System Support for Managing Invalid Bindings

Abstract: Context-aware adaptation is a central aspect of pervasive computing applications, enabling them to adapt and perform tasks based on contextual information. One of the aspects of context-aware adaptation is reconfiguration in which bindings are created between application component and remote services in order to realize new behaviour in response to contextual information. Various research efforts provide reconfiguration support and allow the development of adaptive context-aware applications from high-level specifications, but don't consider failure conditions that might arise during execution of such applications, making bindings between application and remote services invalid. To this end, we propose and implement our design approach to reconfiguration to manage invalid bindings. The development and modification of adaptive context-aware applications is a complex task, and an issue of an invalidity of bindings further complicates development efforts. To reduce the development efforts, our approach provides an application-transparent solution where the issue of the invalidity of bindings is handled by our system, Policy-Based Contextual Reconfiguration and Adaptation (PCRA), not by an application developer. In this paper, we present and describe our approach to managing invalid bindings and compare it with other approaches to this problem. We also provide performance evaluation of our approach.


Collision-resistant hash function based on composition of functions

Abstract: cryptographic hash function is a deterministic procedure that compresses an arbitrary block of numerical data and returns a fixed-size bit string. There exist many hash functions: MD5, HAVAL, SHA, ... It was reported that these hash functions are not longer secure. Our work is focused in the construction of a new hash function based on composition of functions. The construction used the NP-completeness of Three-dimensional contingency tables and the relaxation of the constraint that a hash function should also be a compression function.


Applying Algebraic Specifications on Digital Right Management Systems

Abstract: Digital Right Management (DRM) Systems have been created to meet the need for digital content protection and distribution. In this paper we present some of the directions of our ongoing research to apply algebraic specification techniques on mobile DRM systems.


'Just Enough' Ontology Engineering

Abstract: This paper introduces 'just enough' principles and 'systems engineering' approach to the practice of ontology development to provide a minimal yet complete, lightweight, agile and integrated development process, supportive of stakeholder management and implementation independence.


Knowledge Audit Framework

Abstract: KAF consists of a process and some templates to guide the planning and execution of audits of knowledge resources, with emphasis on sharing. KAF is based on methodological blueprint provided by the Data Audit Framework (DAF)conceived by the JISC-funded DAFD project.KAF enables organisations to find out what knowledge resources are associated with the project, and how they are shared.KAF is available in two versionsKAF-g (generic, domain independent) KAF-se (targets systems enegineering knowledge)


Gender Recognition Based on Sift Features

Abstract: This paper proposes a robust approach for face detection and gender classification in color images. Previous researches about gender recognition suppose an expensive computational and time-consuming pre-processing step in order to alignment in which face images are aligned so that facial landmarks like eyes, nose, lips, chin are placed in uniform locations in image. In this paper, a novel technique based on mathematical analysis is represented in three stages that eliminates alignment step. First, a new color based face detection method is represented with a better result and more robustness in complex backgrounds. Next, the features which are invariant to affine transformations are extracted from each face using scale invariant feature transform (SIFT) method. To evaluate the performance of the proposed algorithm, experiments have been conducted by employing a SVM classifier on a database of face images which contains 500 images from distinct people with equal ratio of male and female.


Evolving A-Type Artificial Neural Networks

Abstract: We investigate Turing's notion of an A-type artificial neural network. We study a refinement of Turing's original idea, motivated by work of Teuscher, Bull, Preen and Copeland. Our A-types can process binary data by accepting and outputting sequences of binary vectors; hence we can associate a function to an A-type, and we say the A-type {\em represents} the function. There are two modes of data processing: clamped and sequential. We describe an evolutionary algorithm, involving graph-theoretic manipulations of A-types, which searches for A-types representing a given function. The algorithm uses both mutation and crossover operators. We implemented the algorithm and applied it to three benchmark tasks. We found that the algorithm performed much better than a random search. For two out of the three tasks, the algorithm with crossover performed better than a mutation-only version.


k-Capture in Multiagent Pursuit Evasion, or the Lion and the Hyenas

Abstract: We consider the following generalization of the classical pursuit-evasion problem, which we call k-capture. A group of n pursuers (hyenas) wish to capture an evader (lion) who is free to move in an m-dimensional Euclidean space, the pursuers and the evader can move with the same maximum speed, and at least k pursuers must simultaneously reach the evader's location to capture it. If fewer than k pursuers reach the evader, then those pursuers get destroyed by the evader. Under what conditions can the evader be k-captured? We study this problem in the discrete time, continuous space model and prove that k-capture is possible if and only there exists a time when the evader lies in the interior of the pursuers' k-Hull. When the pursuit occurs inside a compact, convex subset of the Euclidean space, we show through an easy constructive strategy that k-capture is always possible.


Multilayer Approach to Defend Phishing Attacks

Abstract: Spam messes up users inbox, consumes resources and spread attacks like DDoS, MiM, phishing etc. Phishing is a byproduct of email and causes financial loss to users and loss of reputation to financial institutions. In this paper we examine the characteristics of phishing and technology used by Phishers. In order to counter anti-phishing technology, phishers change their mode of operation; therefore a continuous evaluation of phishing only helps us combat phisher effectiveness. In our study, we collected seven hundred thousand spam from a corporate server for a period of 13 months from February 2008 to February 2009. From the collected data, we identified different kinds of phishing scams and mode of operation. Our observation shows that phishers are dynamic and depend more on social engineering techniques rather than software vulnerabilities. We believe that this study will develop more efficient anti-phishing methodologies. Based on our analysis, we developed an anti-phishing methodology and implemented in our network. The results show that this approach is highly effective to prevent phishing attacks. The proposed approach reduced more than 80% of the false negatives and more than 95% of phishing attacks in our network.


Load Balancing for MapReduce-based Entity Resolution

Abstract: The effectiveness and scalability of MapReduce-based implementations of complex data-intensive tasks depend on an even redistribution of data between map and reduce tasks. In the presence of skewed data, sophisticated redistribution approaches thus become necessary to achieve load balancing among all reduce tasks to be executed in parallel. For the complex problem of entity resolution, we propose and evaluate two approaches for such skew handling and load balancing. The approaches support blocking techniques to reduce the search space of entity resolution, utilize a preprocessing MapReduce job to analyze the data distribution, and distribute the entities of large blocks among multiple reduce tasks. The evaluation on a real cloud infrastructure shows the value and effectiveness of the proposed load balancing approaches.


A new embedding quality assessment method for manifold learning

Abstract: Manifold learning is a hot research topic in the field of computer science. A crucial issue with current manifold learning methods is that they lack a natural quantitative measure to assess the quality of learned embeddings, which greatly limits their applications to real-world problems. In this paper, a new embedding quality assessment method for manifold learning, named as Normalization Independent Embedding Quality Assessment (NIEQA), is proposed. Compared with current assessment methods which are limited to isometric embeddings, the NIEQA method has a much larger application range due to two features. First, it is based on a new measure which can effectively evaluate how well local neighborhood geometry is preserved under normalization, hence it can be applied to both isometric and normalized embeddings. Second, it can provide both local and global evaluations to output an overall assessment. Therefore, NIEQA can serve as a natural tool in model selection and evaluation tasks for manifold learning. Experimental results on benchmark data sets validate the effectiveness of the proposed method.


Efficient Sum-Based Hierarchical Smoothing Under \ell_1-Norm

Abstract: We introduce a new regression problem which we call the Sum-Based Hierarchical Smoothing problem. Given a directed acyclic graph and a non-negative value, called target value, for each vertex in the graph, we wish to find non-negative values for the vertices satisfying a certain constraint while minimizing the distance of these assigned values and the target values in the lp-norm. The constraint is that the value assigned to each vertex should be no less than the sum of the values assigned to its children. We motivate this problem with applications in information retrieval and web mining. While our problem can be solved in polynomial time using linear programming, given the input size in these applications such a solution might be too slow. We mainly study the \ell_1-norm case restricting the underlying graphs to rooted trees. For this case we provide an efficient algorithm, running in O(n^2) time. While the algorithm is purely combinatorial, its proof of correctness is an elegant use of linear programming duality. We believe that our approach may be applicable to similar problems, where comparable hierarchical constraints are involved, e.g. considering the average of the values assigned to the children of each vertex. While similar in flavor to other smoothing problems like Isotonic Regression (see for example [Angelov et al. SODA'06]), our problem is arguably richer and theoretically more challenging.


Randomized Strategyproof Mechanisms for Facility Location and the Mini-Sum-of-Squares Objective

Abstract: We consider the problem of locating a public facility on a line, where a set of $n$ strategic agents report their \emph{locations} and a mechanism determines, either deterministically or randomly, the location of the facility. Game theoretic perspectives of the facility location problem advanced in two main directions. The first direction is concerned with the characterization of \emph{strategyproof} (SP) mechanisms; i.e., mechanisms that induce truthful reporting as a dominant strategy; and the second direction quantifies how well various objective functions can be approximated when restricted to SP mechanisms. The current paper provides contributions in both directions. First, we construct a parameterized randomized SP mechanism, and show that all of the previously proposed deterministic and randomized SP mechanisms for the current settings can be formalized as special cases of this mechanism. Second, we give tight results for the approximation ratio of SP mechanisms with respect to the objective of minimizing the sum of squares of distances to the agents (\emph{miniSOS}). Holzman \cite{Holzman1990} provided an axiomatic foundation for this function, showing that it is the unique function that satisfies unanimity, continuity and invariance. We devise a randomized mechanism that gives a 1.5-approximation for the miniSOS function, and show that no other randomized SP mechanism can provide a better approximation. This mechanism chooses the average location with probability 1/2 and a \emph{random dictator} with probability 1/2. For deterministic mechanisms, we show that the median mechanism provides a 2-approximation, and this is tight. Together, our study provides fundamental understanding of the miniSOS objective function and makes a step toward the characterization of randomized SP facility location mechanisms.


G-NetMon: A GPU-accelerated Network Performance Monitoring System for Large Scale Scientific Collaborations

Abstract: Network traffic is difficult to monitor and analyze, especially in high-bandwidth networks. Performance analysis, in particular, presents extreme complexity and scalability challenges. GPU (Graphics Processing Unit) technology has been utilized recently to accelerate general purpose scientific and engineering computing. GPUs offer extreme thread-level parallelism with hundreds of simple cores. Their data-parallel execution model can rapidly solve large problems with inherent data parallelism. At Fermilab, we have prototyped a GPU-accelerated network performance monitoring system, called G-NetMon, to support large-scale scientific collaborations. In this work, we explore new opportunities in network traffic monitoring and analysis with GPUs. Our system exploits the data parallelism that exists within network flow data to provide fast analysis of bulk data movement between Fermilab and collaboration sites. Experiments demonstrate that our G-NetMon can rapidly detect sub-optimal bulk data movements.


Towards reduction of Paradigm coordination models

Abstract: The coordination modelling language Paradigm addresses collaboration between components in terms of dynamic constraints. Within a Paradigm model, component dynamics are consistently specified at a detailed and a global level of abstraction. To enable automated verification of Paradigm models, a translation of Paradigm into process algebra has been defined in previous work. In this paper we investigate, guided by a client-server example, reduction of Paradigm models based on a notion of global inertness. Representation of Paradigm models as process algebraic specifications helps to establish a property-preserving equivalence relation between the original and the reduced Paradigm model. Experiments indicate that in this way larger Paradigm models can be analyzed.


Input-output Conformance Testing for Channel-based Service Connectors

Abstract: Service-based systems are software systems composed of autonomous components or services provided by different vendors, deployed on remote machines and accessible through the web. One of the challenges of modern software engineering is to ensure that such a system behaves as intended by its designer. The Reo coordination language is an extensible notation for formal modeling and execution of service compositions. Services that have no prior knowledge about each other communicate through advanced channel connectors which guarantee that each participant, service or client, receives the right data at the right time. Each channel is a binary relation that imposes synchronization and data constraints on input and output messages. Furthermore, channels are composed together to realize arbitrarily complex behavioral protocols. During this process, a designer may introduce errors into the connector model or the code for their execution, and thus affect the behavior of a composed service. In this paper, we present an approach for model-based testing of coordination protocols designed in Reo. Our approach is based on the input-output conformance (ioco) testing theory and exploits the mapping of automata-based semantic models for Reo to equivalent process algebra specifications.


A Process Algebra for Supervisory Coordination

Abstract: A supervisory controller controls and coordinates the behavior of different components of a complex machine by observing their discrete behaviour. Supervisory control theory studies automated synthesis of controller models, known as supervisors, based on formal models of the machine components and a formalization of the requirements. Subsequently, code generation can be used to implement this supervisor in software, on a PLC, or embedded microprocessor. In this article, we take a closer look at the control loop that couples the supervisory controller and the machine. We model both event-based and state-based observations using process algebra and bisimulation-based semantics. The main application area of supervisory control that we consider is coordination, referred to as supervisory coordination, and we give an academic and an industrial example, discussing the process-theoretic concepts employed.


Parameterized Verification of Safety Properties in Ad Hoc Network Protocols

Abstract: We summarize the main results proved in recent work on the parameterized verification of safety properties for ad hoc network protocols. We consider a model in which the communication topology of a network is represented as a graph. Nodes represent states of individual processes. Adjacent nodes represent single-hop neighbors. Processes are finite state automata that communicate via selective broadcast messages. Reception of a broadcast is restricted to single-hop neighbors. For this model we consider a decision problem that can be expressed as the verification of the existence of an initial topology in which the execution of the protocol can lead to a configuration with at least one node in a certain state. The decision problem is parametric both on the size and on the form of the communication topology of the initial configurations. We draw a complete picture of the decidability and complexity boundaries of this problem according to various assumptions on the possible topologies.


Uniform Labeled Transition Systems for Nondeterministic, Probabilistic, and Stochastic Process Calculi

Abstract: Labeled transition systems are typically used to represent the behavior of nondeterministic processes, with labeled transitions defining a one-step state to-state reachability relation. This model has been recently made more general by modifying the transition relation in such a way that it associates with any source state and transition label a reachability distribution, i.e., a function mapping each possible target state to a value of some domain that expresses the degree of one-step reachability of that target state. In this extended abstract, we show how the resulting model, called ULTraS from Uniform Labeled Transition System, can be naturally used to give semantics to a fully nondeterministic, a fully probabilistic, and a fully stochastic variant of a CSP-like process language.


Technical Report: Multi-Carrier Position-Based Packet Forwarding Protocol For Wireless Sensor Networks

Abstract: Beaconless position-based forwarding protocols have recently evolved as a promising solution for packet forwarding in wireless sensor networks. However, as the node density grows, the overhead incurred in the process of relay selection grows significantly. As such, end-to-end performance in terms of energy and latency is adversely impacted. With the motivation of developing a packet forwarding mechanism that is tolerant to node density, an alternative position-based protocol is proposed in this paper. In contrast to existing beaconless protocols, the proposed protocol is designed such that it eliminates the need for potential relays to undergo a relay selection process. Rather, any eligible relay may decide to forward the packet ahead, thus significantly reducing the underlying overhead. The operation of the proposed protocol is empowered by exploiting favorable features of orthogonal frequency division multiplexing (OFDM) at the physical layer. The end-to-end performance of the proposed protocol is evaluated against existing beaconless position-based protocols analytically and as well by means of simulations. The proposed protocol is demonstrated in this paper to be more efficient. In particular, it is shown that for the same amount of energy the proposed protocol transports one bit from source to destination much quicker.


Rule-based Construction of Matching Processes

Abstract: Mapping complex metadata structures is crucial in a number of domains such as data integration, ontology alignment or model management. To speed up that process automatic matching systems were developed to compute mapping suggestions that can be corrected by a user. However, constructing and tuning match strategies still requires a high manual effort by matching experts as well as correct mappings to evaluate generated mappings. We therefore propose a self-configuring schema matching system that is able to automatically adapt to the given mapping problem at hand. Our approach is based on analyzing the input schemas as well as intermediate matching results. A variety of matching rules use the analysis results to automatically construct and adapt an underlying matching process for a given match task. We comprehensively evaluate our approach on different mapping problems from the schema, ontology and model management domains. The evaluation shows that our system is able to robustly return good quality mappings across different mapping problems and domains.


Computing a Maximal Independent Set Using Beeps

Abstract: We consider the problem of finding a maximal independent set (MIS) in the discrete beeping model. At each time, a node in the network can either beep (i.e., emit a signal) or be silent. Silent nodes can only differentiate between no neighbor beeping, or at least one neighbor beeping. This basic communication model relies only on carrier-sensing. Furthermore, we assume nothing about the underlying communication graph and allow nodes to wake up (and crash) arbitrarily. We show that if a polynomial upper bound on the size of the network n is known, then with high probability every node becomes stable in O(\log^3 n) time after it is woken up. To contrast this, we establish a polynomial lower bound when no a priori upper bound on the network size is known. This holds even in the much stronger model of local message broadcast with collision detection. Finally, if we assume nodes have access to synchronized clocks or we consider a somewhat restricted wake up, we can solve the MIS problem in O(\log^2 n) time without requiring an upper bound on the size of the network, thereby achieving the same bit complexity as Luby's MIS algorithm.


HybridNN: Supporting Network Location Service on Generalized Delay Metrics

Abstract: Distributed Nearest Neighbor Search (DNNS) locates service nodes that have shortest interactive delay towards requesting hosts. DNNS provides an important service for large-scale latency sensitive networked applications, such as VoIP, online network games, or interactive network services on the cloud. Existing work assumes the delay to be symmetric, which does not generalize to applications that are sensitive to one-way delays, such as the multimedia video delivery from the servers to the hosts. We propose a relaxed inframetric model for the network delay space that does not assume the triangle inequality and delay symmetry to hold. We prove that the DNNS requests can be completed efficiently if the delay space exhibits modest inframetric dimensions, which we can observe empirically. Finally, we propose a DNNS method named HybridNN (\textit{Hybrid} \textit{N}earest \textit{N}eighbor search) based on the inframetric model for fast and accurate DNNS. For DNNS requests, HybridNN chooses closest neighbors accurately via the inframetric modelling, and scalably by combining delay predictions with direct probes to a pruned set of neighbors. Simulation results show that HybridNN locates nearly optimally the nearest neighbor. Experiments on PlanetLab show that HybridNN can provide accurate nearest neighbors that are close to optimal with modest query overhead and maintenance traffic.


Factorization-based Lossless Compression of Inverted Indices

Abstract: Many large-scale Web applications that require ranked top-k retrieval such as Web search and online advertising are implemented using inverted indices. An inverted index represents a sparse term-document matrix, where non-zero elements indicate the strength of term-document association. In this work, we present an approach for lossless compression of inverted indices. Our approach maps terms in a document corpus to a new term space in order to reduce the number of non-zero elements in the term-document matrix, resulting in a more compact inverted index. We formulate the problem of selecting a new term space that minimizes the resulting index size as a matrix factorization problem, and prove that finding the optimal factorization is an NP-hard problem. We develop a greedy algorithm for finding an approximate solution. A side effect of our approach is increasing the number of terms in the index, which may negatively affect query evaluation performance. To eliminate such effect, we develop a methodology for modifying query evaluation algorithms by exploiting specific properties of our compression approach. Our experimental evaluation demonstrates that our approach achieves an index size reduction of 20%, while maintaining the same query response times. Higher compression ratios up to 35% are achievable, however at the cost of slightly longer query response times. Furthermore, combining our approach with other lossless compression techniques, namely variable-byte encoding, leads to index size reduction of up to 50%.


A Concise Query Language with Search and Transform Operations for Corpora with Multiple Levels of Annotation

Abstract: The usefulness of annotated corpora is greatly increased if there is an associated tool that can allow various kinds of operations to be performed in a simple way. Different kinds of annotation frameworks and many query languages for them have been proposed, including some to deal with multiple layers of annotation. We present here an easy to learn query language for a particular kind of annotation framework based on 'threaded trees', which are somewhere between the complete order of a tree and the anarchy of a graph. Through 'typed' threads, they can allow multiple levels of annotation in the same document. Our language has a simple, intuitive and concise syntax and high expressive power. It allows not only to search for complicated patterns with short queries but also allows data manipulation and specification of arbitrary return values. Many of the commonly used tasks that otherwise require writing programs, can be performed with one or more queries. We compare the language with some others and try to evaluate it.


Succinct Representations of Permutations and Functions

Abstract: We investigate the problem of succinctly representing an arbitrary permutation, \pi, on {0,...,n-1} so that \pi^k(i) can be computed quickly for any i and any (positive or negative) integer power k. A representation taking (1+\epsilon) n lg n + O(1) bits suffices to compute arbitrary powers in constant time, for any positive constant \epsilon <= 1. A representation taking the optimal \ceil{\lg n!} + o(n) bits can be used to compute arbitrary powers in O(lg n / lg lg n) time. We then consider the more general problem of succinctly representing an arbitrary function, f: [n] \rightarrow [n] so that f^k(i) can be computed quickly for any i and any integer power k. We give a representation that takes (1+\epsilon) n lg n + O(1) bits, for any positive constant \epsilon <= 1, and computes arbitrary positive powers in constant time. It can also be used to compute f^k(i), for any negative integer k, in optimal O(1+|f^k(i)|) time. We place emphasis on the redundancy, or the space beyond the information-theoretic lower bound that the data structure uses in order to support operations efficiently. A number of lower bounds have recently been shown on the redundancy of data structures. These lower bounds confirm the space-time optimality of some of our solutions. Furthermore, the redundancy of one of our structures "surpasses" a recent lower bound by Golynski [Golynski, SODA 2009], thus demonstrating the limitations of this lower bound.


A Knowledge Mining Model for Ranking Institutions using Rough Computing with Ordering Rules and Formal Concept analysis

Abstract: Emergences of computers and information technological revolution made tremendous changes in the real world and provides a different dimension for the intelligent data analysis. Well formed fact, the information at right time and at right place deploy a better knowledge.However, the challenge arises when larger volume of inconsistent data is given for decision making and knowledge extraction. To handle such imprecise data certain mathematical tools of greater importance has developed by researches in recent past namely fuzzy set, intuitionistic fuzzy set, rough Set, formal concept analysis and ordering rules. It is also observed that many information system contains numerical attribute values and therefore they are almost similar instead of exact similar. To handle such type of information system, in this paper we use two processes such as pre process and post process. In pre process we use rough set on intuitionistic fuzzy approximation space with ordering rules for finding the knowledge whereas in post process we use formal concept analysis to explore better knowledge and vital factors affecting decisions.


Uncertain Nearest Neighbor Classification

Abstract: This work deals with the problem of classifying uncertain data. With this aim the Uncertain Nearest Neighbor (UNN) rule is here introduced, which represents the generalization of the deterministic nearest neighbor rule to the case in which uncertain objects are available. The UNN rule relies on the concept of nearest neighbor class, rather than on that of nearest neighbor object. The nearest neighbor class of a test object is the class that maximizes the probability of providing its nearest neighbor. It is provided evidence that the former concept is much more powerful than the latter one in the presence of uncertainty, in that it correctly models the right semantics of the nearest neighbor decision rule when applied to the uncertain scenario. An effective and efficient algorithm to perform uncertain nearest neighbor classification of a generic (un)certain test object is designed, based on properties that greatly reduce the temporal cost associated with nearest neighbor class probability computation. Experimental results are presented, showing that the UNN rule is effective and efficient in classifying uncertain data.


Witness Rectangle Graphs

Abstract: In a witness rectangle graph (WRG) on vertex point set P with respect to witness points set W in the plane, two points x, y in P are adjacent whenever the open isothetic rectangle with x and y as opposite corners contains at least one point in W. WRGs are representative of a a larger family of witness proximity graphs introduced in two previous papers. We study graph-theoretic properties of WRGs. We prove that any WRG has at most two non-trivial connected components. We bound the diameter of the non-trivial connected components of a WRG in both the one-component and two-component cases. In the latter case, we prove that a graph is representable as a WRG if and only if each component is a connected co-interval graph, thereby providing a complete characterization of WRGs of this type. We also completely characterize trees drawable as WRGs. In addition, we prove that a WRG with no isolated vertices has domination number at most four. Moreover, we show that any combinatorial graph can be drawn as a WRG using a combination of positive and negative witnesses. Finally we conclude with some related results on the number of points required to stab all the rectangles defined by a set of n point.


How to Cover a Point Set with a V-Shape of Minimum Width

Abstract: A balanced V-shape is a polygonal region in the plane contained in the union of two crossing equal-width strips. It is delimited by two pairs of parallel rays that emanate from two points x, y, are contained in the strip boundaries, and are mirror-symmetric with respect to the line xy. The width of a balanced V-shape is the width of the strips. We first present an O(n^2 log n) time algorithm to compute, given a set of n points P, a minimum-width balanced V-shape covering P. We then describe a PTAS for computing a (1+epsilon)-approximation of this V-shape in time O((n/epsilon)log n+(n/epsilon^(3/2))log^2(1/epsilon)). A much simpler constant-factor approximation algorithm is also described.


Can User-Level Probing Detect and Diagnose Common Home-WLAN Pathologies?

Abstract: Common WLAN pathologies include low signal-to-noise ratio, congestion, hidden terminals or interference from non-802.11 devices and phenomena. Prior work has focused on the detection and diagnosis of such problems using layer-2 information from 802.11 devices and special-purpose access points and monitors, which may not be generally available. Here, we investigate a userlevel approach: is it possible to detect and diagnose 802.11 pathologies with strictly user-level active probing, without any cooperation from, and without any visibility in, layer-2 devices? In this paper, we present preliminary but promising results indicating that such diagnostics are feasible.


Going Beyond Pollution Attacks: Forcing Byzantine Clients to Code Correctly

Abstract: Network coding achieves optimal throughput in multicast networks. However, throughput optimality \emph{relies} on the network nodes or routers to code \emph{correctly}. A Byzantine node may introduce junk packets in the network (thus polluting downstream packets and causing the sinks to receive the wrong data) or may choose coding coefficients in a way that significantly reduces the throughput of the network. Most prior work focused on the problem of Byzantine nodes polluting packets. However, even if a Byzantine node does not pollute packets, he can still affect significantly the throughput of the network by not coding correctly. No previous work attempted to verify if a certain node \emph{coded correctly using random coefficients} over \emph{all} of the packets he was supposed to code over. We provide two novel protocols (which we call PIP and Log-PIP) for detecting whether a node coded correctly over all the packets received (i.e., according to a random linear network coding algorithm). Our protocols enable any node in the network to examine a packet received from another node by running a "verification test". With our protocols, the worst an adversary can do and still pass the packet verification test is in fact equivalent to random linear network coding, which has been shown to be optimal in multicast networks. Our protocols resist collusion among nodes and are applicable to a variety of settings. Our topology simulations show that the throughput in the worst case for our protocol is two to three times larger than the throughput in various adversarial strategies allowed by prior work. We implemented our protocols in C/C++ and Java, as well as incorporated them on the Android platform (Nexus One). Our evaluation shows that our protocols impose modest overhead.


Proceedings 7th International Workshop on Automated Specification and Verification of Web Systems

Abstract: This volume contains the final and revised versions of the papers presented at the 7th International Workshop on Automated Specification and Verification of Web Systems (WWV 2011). The workshop was held in Reykjavik, Iceland, on June 9, 2011, as part of DisCoTec 2011. The aim of the WWV workshop series is to provide an interdisciplinary forum to facilitate the cross-fertilization and the advancement of hybrid methods that exploit concepts and tools drawn from Rule-based programming, Software engineering, Formal methods and Web-oriented research. Nowadays, indeed, many companies and institutions have diverted their Web sites into interactive, completely-automated, Web-based applications for, e.g., e-business, e-learning, e-government, and e-health. The increased complexity and the explosive growth of Web systems have made their design and implementation a challenging task. Systematic, formal approaches to their specification and verification can permit to address the problems of this specific domain by means of automated and effective techniques and tools. In response to this year's call for papers, we received 9 paper submissions. The Program Committee of WWV 2011 collected three reviews for each paper and held an electronic discussion leading to the selection of 7 papers for presentation at the workshop. In addition to the selected papers, the scientific programme included an invited lecture by Elie Najm.


On the Structure of Weakly Acyclic Games

Abstract: The class of weakly acyclic games, which includes potential games and dominance-solvable games, captures many practical application domains. In a weakly acyclic game, from any starting state, there is a sequence of better-response moves that leads to a pure Nash equilibrium; informally, these are games in which natural distributed dynamics, such as better-response dynamics, cannot enter inescapable oscillations. We establish a novel link between such games and the existence of pure Nash equilibria in subgames. Specifically, we show that the existence of a unique pure Nash equilibrium in every subgame implies the weak acyclicity of a game. In contrast, the possible existence of multiple pure Nash equilibria in every subgame is insufficient for weak acyclicity in general; here, we also systematically identify the special cases (in terms of the number of players and strategies) for which this is sufficient to guarantee weak acyclicity.


A Comparative Study of Various Routing Protocols in VANET

Abstract: Vehicular Ad Hoc Networks (VANET) is a subclass of Mobile ad hoc networks which provides a distinguished approach for Intelligent Transport System (ITS). The survey of routing protocols in VANET is important and necessary for smart ITS. This paper discusses the advantages / disadvantages and the applications of various routing protocols for vehicular ad hoc networks. It explores the motivation behind the designed, and traces the evolution of these routing protocols. F inally the paper concludes by a tabular comparison of the various routing protocols for VANET.


Mobile Agent as an Approach to Improve QoS in Vehicular Ad Hoc Network

Abstract: Vehicular traffic is a foremost problem in modern cities. Huge amount of time and resources are wasted while traveling due to traffic congestion. With the introduction of sophisticated traffic management systems, such as those incorporating dynamic traffic assignments, more stringent demands are being placed upon the available real time traffic data. In this paper we have proposed mobile agent as a mechanism to handle the traffic problem on road. Mobile software agents can be used to provide the better QoS (Quality of Service) in vehicular ad hoc network to improve the safety application and driver comfort.


Privacy Preserving Data Aggregation in Wireless Sensor Networks

Abstract: Privacy preservation is an important issue in today's context of extreme penetration of internet and mobile technologies. It is more important in the case of Wireless Sensor Networks (WSNs) where collected data often requires in-network processing and collaborative computing. Researches in this area are mostly concentrated in applying data mining techniques to preserve the privacy content of the data. These techniques are mostly computationally expensive and not suitable for resource limited WSN nodes. In this paper, a scheme is developed to provide privacy preservation in a much simpler way with the help of a secure key management scheme and randomized data perturbation technique. We consider a scenario in which two or more parties owning confidential data need to share only for aggregation purpose to a third party, without revealing the content of the data. Through simulation results the efficacy of our scheme and compare the result with one of the established scheme [1].


Context Protecting Privacy Preservation in Ubiquitous Computing

Abstract: In ubiquitous computing domain context awareness is an important issue. So, in ubiquitous computing, mere protection of message confidentiality is not sufficient for most of the applications where context-awareness can lead to near deterministic ideas. An adversary might deduce sensitive information by observing the contextual data, which when correlated with prior information about the people and the physical locations that are being monitored by a set of sensors can reveal most of the sensitive information. So, it is obvious that for security and privacy preservation in ubiquitous computing context protection is of equal importance. In this paper, we propose a scheme which provides two layer privacy protection of user's or application's context data. Our proposed context protecting privacy preservation scheme focuses on protecting spatial and temporal contextual information. We consider the communication part of ubiquitous computing consists of tiny sensor nodes forming Wireless Sensor Networks (WSNs). Through simulation we show the efficacy of our scheme. We also demonstrate the capability of our scheme to overcome the constraints of WSNs.


The Ditmarsch Tale of Wonders - The Dynamics of Lying

Abstract: We propose a dynamic logic of lying, wherein a 'lie that phi' (where phi is a formula in the logic) is an action in the sense of dynamic modal logic, that is interpreted as a state transformer relative to the formula phi. The states that are being transformed are pointed Kripke models encoding the uncertainty of agents about their beliefs. Lies can be about factual propositions but also about modal formulas, such as the beliefs of other agents or the belief consequences of the lies of other agents. We distinguish (i) an outside observer who is lying to an agent that is modelled in the system, from (ii) one agent who is lying to another agent, and where both are modelled in the system. For either case, we further distinguish (iii) the agent who believes everything that it is told (even at the price of inconsistency), from (iv) the agent who only believes what it is told if that is consistent with its current beliefs, and from (v) the agent who believes everything that it is told by consistently revising its current beliefs. The logics have complete axiomatizations, which can most elegantly be shown by way of their embedding in what is known as action model logic or the extension of that logic to belief revision.


User Awareness Measurement Through Social Engineering

Abstract: TUBITAK National Research Institute of Electronics and Cryptology (UEKAE) Department of Information Systems Security makes social engineering attacks to Turkish public agencies within the frame of "Information Security Tests" [19]. This paper will make an analysis of the social engineering tests that have been carried out in several Turkish public agencies. The tests include phone calling to sample employees by the social engineer and trying to seize employees' sensitive information by exploiting their good faith. The aim of this research is to figure that the employees in Turkish public agencies have a lack of information security awareness and they compromise the information security principles which should be necessarily applied for any public agencies. Social engineering, both with its low cost and ability to take advantage of low technology, has taken its place in the information security literature as a very effective form of attack [8].


Governing Information Security in Conjunction with COBIT and ISO 27001

Abstract: In this paper, after giving a brief definition of Information Security Management Systems (ISMS), ISO 27001, IT governance and COBIT, pros and cons of implementing only COBIT, implementing only IS0 27001 and implementing both COBIT and ISO 27001 together when governing information security in enterprises will be issued.


Digital Forensics Analysis of Spectral Estimation Methods

Abstract: Steganography is the art and science of writing hidden messages in such a way that no one apart from the intended recipient knows of the existence of the message. In today's world, it is widely used in order to secure the information. In this paper, the traditional spectral estimation methods are introduced. The performance analysis of each method is examined by comparing all of the spectral estimation methods. Finally, from utilizing those performance analyses, a brief pros and cons of the spectral estimation methods are given. Also we give a steganography demo by hiding information into a sound signal and manage to pull out the information (i.e, the true frequency of the information signal) from the sound by means of the spectral estimation methods.


Spectral Estimation Methods Comparison and Performance Analysis on a Steganalysis Application


Analysis and Implementation of Distinct Steganographic Methods

Abstract: In this paper, different steganographic methods have been analyzed and implementations of those techniques have been performed. Those methods include hiding in text, hiding in audio file, hiding in file system, and hiding in image files.


Optimal Indexes for Sparse Bit Vectors

Abstract: We consider the problem of supporting Rank() and Select() operations on a bit vector of length m with n 1 bits. The problem is considered in the succinct index model, where the bit vector is stored in "read-only" memory and an additional data structure, called the index, is created during pre-processing to help answer the above queries. We give asymptotically optimal density-sensitive trade-offs, involving both m and n, that relate the size of the index to the number of accesses to the bit vector (and processing time) needed to answer the above queries. The results are particularly interesting for the case where n = o(m).


Partner selection in indoor-to-outdoor cooperative networks: an experimental study

Abstract: In this paper, we develop a partner selection protocol for enhancing the network lifetime in cooperative wireless networks. The case-study is the cooperative relayed transmission from fixed indoor nodes to a common outdoor access point. A stochastic bivariate model for the spatial distribution of the fading parameters that govern the link performance, namely the Rician K-factor and the path-loss, is proposed and validated by means of real channel measurements. The partner selection protocol is based on the real-time estimation of a function of these fading parameters, i.e., the coding gain. To reduce the complexity of the link quality assessment, a Bayesian approach is proposed that uses the site-specific bivariate model as a-priori information for the coding gain estimation. This link quality estimator allows network lifetime gains almost as if all K-factor values were known. Furthermore, it suits IEEE 802.15.4 compliant networks as it efficiently exploits the information acquired from the receiver signal strength indicator. Extensive numerical results highlight the trade-off between complexity, robustness to model mismatches and network lifetime performance. We show for instance that infrequent updates of the site-specific model through K-factor estimation over a subset of links are sufficient to at least double the network lifetime with respect to existing algorithms based on path loss information only.


Graph and Election Problems Parameterized by Feedback Set Numbers

Abstract: This work investigates the parameterized complexity of three related graph modification problems. Given a directed graph, a distinguished vertex, and a positive integer k, Minimum Indegree Deletion asks for a vertex subset of size at most k whose removal makes the distinguished vertex the only vertex with minimum indegree. Minimum Degree Deletion is analogously defined, but deals with undirected graphs. Bounded Degree Deletion is also defined on undirected graphs, but has a positive integer d instead of a distinguished vertex as part of the input. It asks for a vertex subset of size at most k whose removal results in a graph in which every vertex has degree at most d. The first two problems have applications in computational social choice whereas the third problem is used in computational biology. We investigate the parameterized complexity with respect to the parameters "treewidth", "size of a feedback vertex set" and "size of a feedback edge set" respectively "size of a feedback arc set". Each of these parameters measures the "degree of acyclicity" in different ways.


A survey on independence-based Markov networks learning

Abstract: This work reports the most relevant technical aspects in the problem of learning the \emph{Markov network structure} from data. Such problem has become increasingly important in machine learning, and many other application fields of machine learning. Markov networks, together with Bayesian networks, are probabilistic graphical models, a widely used formalism for handling probability distributions in intelligent systems. Learning graphical models from data have been extensively applied for the case of Bayesian networks, but for Markov networks learning it is not tractable in practice. However, this situation is changing with time, given the exponential growth of computers capacity, the plethora of available digital data, and the researching on new learning technologies. This work stresses on a technology called independence-based learning, which allows the learning of the independence structure of those networks from data in an efficient and sound manner, whenever the dataset is sufficiently large, and data is a representative sampling of the target distribution. In the analysis of such technology, this work surveys the current state-of-the-art algorithms for learning Markov networks structure, discussing its current limitations, and proposing a series of open problems where future works may produce some advances in the area in terms of quality and efficiency. The paper concludes by opening a discussion about how to develop a general formalism for improving the quality of the structures learned, when data is scarce.


A theorem proving framework for the formal verification of Web Services Composition

Abstract: We present a rigorous framework for the composition of Web Services within a higher order logic theorem prover. Our approach is based on the proofs-as-processes paradigm that enables inference rules of Classical Linear Logic (CLL) to be translated into pi-calculus processes. In this setting, composition is achieved by representing available web services as CLL sentences, proving the requested composite service as a conjecture, and then extracting the constructed pi-calculus term from the proof. Our framework, implemented in HOL Light, not only uses an expressive logic that allows us to incorporate multiple Web Services properties in the composition process, but also provides guarantees of soundness and correctness for the composition.


Specification and Verification of Context-dependent Services

Abstract: Current approaches for the discovery, specification, and provision of services ignore the relationship between the service contract and the conditions in which the service can guarantee its contract. Moreover, they do not use formal methods for specifying services, contracts, and compositions. Without a formal basis it is not possible to justify through formal verification the correctness conditions for service compositions and the satisfaction of contractual obligations in service provisions. We remedy this situation in this paper. We present a formal definition of services with context-dependent contracts. We define a composition theory of services with context-dependent contracts taking into consideration functional, nonfunctional, legal and contextual information. Finally, we present a formal verification approach that transforms the formal specification of service composition into extended timed automata that can be verified using the model checking tool UPPAAL.


Product Lines for Service Oriented Applications - PL for SOA

Abstract: PL for SOA proposes, formally, a software engineering methodology, development techniques and support tools for the provision of service product lines. We propose rigorous modeling techniques for the specification and verification of formal notations and languages for service computing with inclinations of variability. Through these cutting-edge technologies, increased levels of flexibility and adaptivity can be achieved. This will involve developing semantics of variability over behavioural models of services. Such tools will assist organizations to plan, optimize and control the quality of software service provision, both at design and at run time by making it possible to develop flexible and cost-effective software systems that support high levels of reuse. We tackle this challenge from two levels. We use feature modeling from product line engineering and, from a services point of view, the orchestration language Orc. We introduce the Smart Grid as the service product line to apply the techniques to.


Automated Functional Testing based on the Navigation of Web Applications

Abstract: Web applications are becoming more and more complex. Testing such applications is an intricate hard and time-consuming activity. Therefore, testing is often poorly performed or skipped by practitioners. Test automation can help to avoid this situation. Hence, this paper presents a novel approach to perform automated software testing for web applications based on its navigation. On the one hand, web navigation is the process of traversing a web application using a browser. On the other hand, functional requirements are actions that an application must do. Therefore, the evaluation of the correct navigation of web applications results in the assessment of the specified functional requirements. The proposed method to perform the automation is done in four levels: test case generation, test data derivation, test case execution, and test case reporting. This method is driven by three kinds of inputs: i) UML models; ii) Selenium scripts; iii) XML files. We have implemented our approach in an open-source testing framework named Automatic Testing Platform. The validation of this work has been carried out by means of a case study, in which the target is a real invoice management system developed using a model-driven approach.


Debugging of Web Applications with Web-TLR

Abstract: Web-TLR is a Web verification engine that is based on the well-established Rewriting Logic--Maude/LTLR tandem for Web system specification and model-checking. In Web-TLR, Web applications are expressed as rewrite theories that can be formally verified by using the Maude built-in LTLR model-checker. Whenever a property is refuted, a counterexample trace is delivered that reveals an undesired, erroneous navigation sequence. Unfortunately, the analysis (or even the simple inspection) of such counterexamples may be unfeasible because of the size and complexity of the traces under examination. In this paper, we endow Web-TLR with a new Web debugging facility that supports the efficient manipulation of counterexample traces. This facility is based on a backward trace-slicing technique for rewriting logic theories that allows the pieces of information that we are interested to be traced back through inverse rewrite sequences. The slicing process drastically simplifies the computation trace by dropping useless data that do not influence the final result. By using this facility, the Web engineer can focus on the relevant fragments of the failing application, which greatly reduces the manual debugging effort and also decreases the number of iterative verifications.


An Abstract Semantics for Inference of Types and Effects in a Multi-Tier Web Language

Abstract: Types-and-effects are type systems, which allow one to express general semantic properties and to statically reason about program's execution. They have been widely exploited to specify static analyses, for example to track computational side effects, exceptions and communications in concurrent programs. In this paper we adopt abstract interpretation techniques to reconstruct (following the Cousot's methodology) a types-and-effects system developed to handle security problems of a multi-tier web language. Our reconstruction allows us to show that this types-and-effects system is not sound with respect to the semantics of the language. In addition, we correct the soundness issues in the analysis and systematically construct a correct analyser.


A type checking algorithm for qualified session types

Abstract: We present a type checking algorithm for establishing a session-based discipline in the pi calculus of Milner, Parrow and Walker. Our session types are qualified as linear or unrestricted. Linearly typed communication channels are guaranteed to occur in exactly one thread, possibly multiple times; afterwards they evolve as unrestricted channels. Session protocols are described by a type constructor that denotes the two ends of one and the same communication channel. We ensure the soundness of the algorithm by showing that processes consuming all linear resources are accepted by a type system preserving typings during the computation and that type checking is consistent w.r.t. structural congruence.


Maximal Structuring of Acyclic Process Models

Abstract: This paper contributes to the solution of the problem of transforming a process model with an arbitrary topology into an equivalent structured process model. In particular, this paper addresses the subclass of process models that have no equivalent well-structured representation but which, nevertheless, can be partially structured into their maximally-structured representation. The structuring is performed under a behavioral equivalence notion that preserves observed concurrency of tasks in equivalent process models. The paper gives a full characterization of the subclass of acyclic process models that have no equivalent well-structured representation but do have an equivalent maximally-structured one, as well as proposes a complete structuring method.


Width-parameterized SAT: Time-Space Tradeoffs

Abstract: Width parameterizations of SAT, such as tree-width and path-width, enable the study of computationally more tractable and practical SAT instances. We give two simple algorithms. One that runs simultaneously in time-space $(O^*(2^{2tw(\phi)}), O^*(2^{tw(\phi)}))$ and another that runs in time-space $(O^*(3^{tw(\phi)\log{|\phi|}}),|\phi|^{O(1)})$, where $tw(\phi)$ is the tree-width of a formula $\phi$ with $|\phi|$ many clauses and variables. This partially answers the question of Alekhnovitch and Razborov, who also gave algorithms exponential both in time and space, and asked whether the space can be made smaller. We conjecture that every algorithm for this problem that runs in time $2^{tw(\phi)\mathbf{o(\log{|\phi|})}}$ necessarily blows up the space to exponential in $tw(\phi)$. We introduce a novel way to combine the two simple algorithms that allows us to trade \emph{constant} factors in the exponents between running time and space. Our technique gives rise to a family of algorithms controlled by two parameters. By fixing one parameter we obtain an algorithm that runs in time-space $(O^*(3^{1.441(1-\epsilon)tw(\phi)\log{|\phi|}}), O^*(2^{2\epsilon tw(\phi)}))$, for every $0<\epsilon<1$. We systematically study the limitations of this technique, and show that these algorithmic results are the best achievable using this technique. We also study further the computational complexity of width parameterizations of SAT. We prove non-sparsification lower bounds for formulas of path-width $\omega(\log|\phi|)$, and a separation between the complexity of path-width and tree-width parametrized SAT modulo plausible complexity assumptions.


A New System Architecture for Pervasive Computing

Abstract: We present new system architecture, a distributed framework designed to support pervasive computing applications. We propose a new architecture consisting of a search engine and peripheral clients that addresses issues in scalability, data sharing, data transformation and inherent platform heterogeneity. Key features of our application are a type-aware data transport that is capable of extract data, and present data through handheld devices (PDA (personal digital assistant), mobiles, etc). Pervasive computing uses web technology, portable devices, wireless communications and nomadic or ubiquitous computing systems. The web and the simple standard HTTP protocol that it is based on, facilitate this kind of ubiquitous access. This can be implemented on a variety of devices - PDAs, laptops, information appliances such as digital cameras and printers. Mobile users get transparent access to resources outside their current environment. We discuss our system's architecture and its implementation. Through experimental study, we show reasonable performance and adaptation for our system's implementation for the mobile devices.


Deciding Regularity of Hairpin Completions of Regular Languages in Polynomial Time

Abstract: The hairpin completion is an operation on formal languages that has been inspired by the hairpin formation in DNA biochemistry and by DNA computing. In this paper we investigate the hairpin completion of regular languages. It is well known that hairpin completions of regular languages are linear context-free and not necessarily regular. As regularity of a (linear) context-free language is not decidable, the question arose whether regularity of a hairpin completion of regular languages is decidable. We prove that this problem is decidable and we provide a polynomial time algorithm. Furthermore, we prove that the hairpin completion of regular languages is an unambiguous linear context-free language and, as such, it has an effectively computable growth function. Moreover, we show that the growth of the hairpin completion is exponential if and only if the growth of the underlying languages is exponential and, in case the hairpin completion is regular, then the hairpin completion and the underlying languages have the same growth indicator.


Sequential Auctions and Externalities

Abstract: In many settings agents participate in multiple different auctions that are not necessarily implemented simultaneously. Future opportunities affect strategic considerations of the players in each auction, introducing externalities. Motivated by this consideration, we study a setting of a market of buyers and sellers, where each seller holds one item, bidders have combinatorial valuations and sellers hold item auctions sequentially. Our results are qualitatively different from those of simultaneous auctions, proving that simultaneity is a crucial aspect of previous work. We prove that if sellers hold sequential first price auctions then for unit-demand bidders (matching market) every subgame perfect equilibrium achieves at least half of the optimal social welfare, while for submodular bidders or when second price auctions are used, the social welfare can be arbitrarily worse than the optimal. We also show that a first price sequential auction for buying or selling a base of a matroid is always efficient, and implements the VCG outcome. An important tool in our analysis is studying first and second price auctions with externalities (bidders have valuations for each possible winner outcome), which can be of independent interest. We show that a Pure Nash Equilibrium always exists in a first price auction with externalities.


Cryptovirology: Virus Approach

Abstract: Traditionally, "Cryptography" is a benediction to information processing and communications, it helps people to store information securely and the private communications over long distances. Cryptovirology is the study of applications of cryptography to build the malicious software. It is an investigation, how modern cryptographic tools and paradigms can be used to strengthen, develop and improve new malicious software attacks. Cryptovirology attacks have been categorized as : give malware enhanced privacy and be more robust against reverse-engineering, secondly give the attacker enhanced anonymity while communicating with deployed malware. This paper presents the idea of "Cryptovirology" which introduce a twist on how cryptography can also be used offensively. Being offensive means, it can be used to mount extortion based attacks that cause loss of access to information, loss of confidentiality, and information leakage, tasks which cryptography usually prevents. Also analyze threats and attacks that misuse of cryptography can cause when combined with fraudulent software (viruses, Trojans). Public-key cryptography is very essential for the attacks that based on cryptovirology. This paper also suggest some of the countermeasures, mechanisms to cope with and prevent such attacks. Even if the attackers actions on the host machine are being monitored, it still cannot be proven beyond reasonable doubt that he or she is the attacker; and it is an "originator-concealing attack". Evidence should be collected from the "author's own system which was used for the attack". These attacks have implications on how the use of cryptographic tools and techniques should be audited and managed in general purpose computing environments, and imply that access to the cryptographic tools should be in well control of the system(such as API routines).


Feature Extraction for Change-Point Detection using Stationary Subspace Analysis

Abstract: Detecting changes in high-dimensional time series is difficult because it involves the comparison of probability densities that need to be estimated from finite samples. In this paper, we present the first feature extraction method tailored to change point detection, which is based on an extended version of Stationary Subspace Analysis. We reduce the dimensionality of the data to the most non-stationary directions, which are most informative for detecting state changes in the time series. In extensive simulations on synthetic data we show that the accuracy of three change point detection algorithms is significantly increased by a prior feature extraction step. These findings are confirmed in an application to industrial fault monitoring.


Effects of MAC Approaches on Non-Monotonic Saturation with COPE - A Simple Case Study

Abstract: We construct a simple network model to provide insight into network design strategies. We show that the model can be used to address various approaches to network coding, MAC, and multi-packet reception so that their effects on network throughput can be evaluated. We consider several topology components which exhibit the same non-monotonic saturation behavior found within the Katti et. al. COPE experiments. We further show that fairness allocation by the MAC can seriously impact performance and cause this non-monotonic saturation. Using our model, we develop a MAC that provides monotonic saturation, higher saturation throughput gains and fairness among flows rather than nodes. The proposed model provides an estimate of the achievable gains for the cross-layer design of network coding, multi-packet reception, and MAC showing that super-additive throughput gains on the order of six times that of routing are possible.


Efficient Multicore Collaborative Filtering

Abstract: This paper describes the solution method taken by LeBuSiShu team for track1 in ACM KDD CUP 2011 contest (resulting in the 5th place). We identified two main challenges: the unique item taxonomy characteristics as well as the large data set size.To handle the item taxonomy, we present a novel method called Matrix Factorization Item Taxonomy Regularization (MFITR). MFITR obtained the 2nd best prediction result out of more then ten implemented algorithms. For rapidly computing multiple solutions of various algorithms, we have implemented an open source parallel collaborative filtering library on top of the GraphLab machine learning framework. We report some preliminary performance results obtained using the BlackLight supercomputer.


Tensor-Based Link Prediction in Intermittently Connected Wireless Networks

Abstract: Through several studies, it has been highlighted that mobility patterns in mobile networks are driven by human behaviors. This effect has been particularly observed in intermittently connected networks like DTN (Delay Tolerant Networks). Given that common social intentions generate similar human behavior, it is relevant to exploit this knowledge in the network protocols design, e.g. to identify the closeness degree between two nodes. In this paper, we propose a temporal link prediction technique for DTN which quantifies the behavior similarity between each pair of nodes and makes use of it to predict future links. Our prediction method keeps track of the spatio-temporal aspects of nodes behaviors organized as a third-order tensor that aims to records the evolution of the network topology. After collapsing the tensor information, we compute the degree of similarity for each pair of nodes using the Katz measure. This metric gives us an indication on the link occurrence between two nodes relying on their closeness. We show the efficiency of this method by applying it on three mobility traces: two real traces and one synthetic trace. Through several simulations, we demonstrate the effectiveness of the technique regarding another approach based on a similarity metric used in DTN. The validity of this method is proven when the computation of score is made in a distributed way (i.e. with local information). We attest that the tensor-based technique is effective for temporal link prediction applied to the intermittently connected networks. Furthermore, we think that this technique can go beyond the realm of DTN and we believe this can be further applied on every case of figure in which there is a need to derive the underlying social structure of a network of mobile users.


Tight bounds for the space complexity of nonregular language recognition by real-time machines

Abstract: We examine the minimum amount of memory for real-time, as opposed to one-way, computation accepting nonregular languages. We consider deterministic, nondeterministic and alternating machines working within strong, middle and weak space, and processing general or unary inputs. In most cases, we are able to show that the lower bounds for one-way machines remain tight in the real-time case. Memory lower bounds for nonregular acceptance on other devices are also addressed. It is shown that increasing the number of stacks of real-time pushdown automata can result in exponential improvement in the total amount of space usage for nonregular language recognition.


Compressive Imaging using Approximate Message Passing and a Markov-Tree Prior

Abstract: We propose a novel algorithm for compressive imaging that exploits both the sparsity and persistence across scales found in the 2D wavelet transform coefficients of natural images. Like other recent works, we model wavelet structure using a hidden Markov tree (HMT) but, unlike other works, ours is based on loopy belief propagation (LBP). For LBP, we adopt a recently proposed "turbo" message passing schedule that alternates between exploitation of HMT structure and exploitation of compressive-measurement structure. For the latter, we leverage Donoho, Maleki, and Montanari's recently proposed approximate message passing (AMP) algorithm. Experiments with a large image database suggest that, relative to existing schemes, our turbo LBP approach yields state-of-the-art reconstruction performance with substantial reduction in complexity.


Classification of Emergency Scenarios

Abstract: In most of today's emergency scenarios information plays a crucial role. Therefore, information has to be constantly collected and shared among all rescue team members and this requires new innovative technologies. In this paper a classification of emergency scenarios is presented, describing their special characteristics and common strategies employed by rescue units to handle them. Based on interviews with professional firefighters, requirements for new systems are listed. The goal of this article is to support developers designing new systems by providing them a deeper look into the work of first responders.


Data Accuracy Model for Distributed Clustering Algorithm based on Spatial Data Correlation in Wireless Sensor Networks

Abstract: Objective: The main objective of this paper is to construct a distributed clustering algorithm based upon spatial data correlation among sensor nodes and perform data accuracy for each distributed cluster at their respective cluster head node. Design Procedure/Approach: We investigate that due to deployment of high density of sensor nodes in the sensor field, spatial data are highly correlated among sensor nodes in spatial domain. Based on high data correlation among sensor nodes, we propose a non -overlapping irregular distributed clustering algorithm with different sizes to collect most accurate or precise data at the cluster head node for each respective distributed cluster. To collect the most accurate data at the cluster head node for each distributed cluster in sensor field, we propose a Data accuracy model and compare the results with Information accuracy model. Finding: Simulation results shows that our propose Data accuracy model collects more accurate data and gives better performance than Information accuracy model at the cluster head node for each respective distributed cluster in our propose distributed clustering algorithm.Morover there exist a optimal cluster of sensor nodes which is adequate to perform approximately the same data accuracy achieve by a cluster. Practical Implementation: Measuring humidity and moisture content in an agricultural field, measuring temperature in physical environment. Inventive /Novel Idea: A distributed clustering algorithm is proposed based on spatial data correlation among sensor nodes with Data accuracy model.


Novel hybrid intrusion detection system for clustered wireless sensor network

Abstract: Wireless sensor network (WSN) is regularly deployed in unattended and hostile environments. The WSN is vulnerable to security threats and susceptible to physical capture. Thus, it is necessary to use effective mechanisms to protect the network. It is widely known, that the intrusion detection is one of the most efficient security mechanisms to protect the network against malicious attacks or unauthorized access. In this paper, we propose a hybrid intrusion detection system for clustered WSN. Our intrusion framework uses a combination between the Anomaly Detection based on support vector machine (SVM) and the Misuse Detection. Experiments results show that most of routing attacks can be detected with low false alarm.


Improving bit-vector representation of points-to sets using class hierarchy

Abstract: Points-to analysis is the problem of approximating run-time values of pointers statically or at compile-time. Points-to sets are used to store the approximated values of pointers during points-to analysis. Memory usage and running time limit the ability of points-to analysis to analyze large programs. To our knowledge, works which have implemented a bit-vector representation of points-to sets so far, allocates bits for each pointer without considering pointer's type. By considering the type, we are able to allocate bits only for a subset of all abstract objects which are of compatible type with the pointer's type and as a consequence improve the memory usage and running time. To achieve this goal, we number abstract objects in a way that all the abstract objects of a type and all of its sub-types be consecutive in order. Our most efficient implementation uses about 2.5 times less memory than hybrid points-to set (default points-to set in Spark) and also improves the analysis time for sufficiently large programs.


Efficient Query Rewrite for Structured Web Queries

Abstract: Web search engines and specialized online verticals are increasingly incorporating results from structured data sources to answer semantically rich user queries. For example, the query \WebQuery{Samsung 50 inch led tv} can be answered using information from a table of television data. However, the users are not domain experts and quite often enter values that do not match precisely the underlying data. Samsung makes 46- or 55- inch led tvs, but not 50-inch ones. So a literal execution of the above mentioned query will return zero results. For optimal user experience, a search engine would prefer to return at least a minimum number of results as close to the original query as possible. Furthermore, due to typical fast retrieval speeds in web-search, a search engine query execution is time-bound. In this paper, we address these challenges by proposing algorithms that rewrite the user query in a principled manner, surfacing at least the required number of results while satisfying the low-latency constraint. We formalize these requirements and introduce a general formulation of the problem. We show that under a natural formulation, the problem is NP-Hard to solve optimally, and present approximation algorithms that produce good rewrites. We empirically validate our algorithms on large-scale data obtained from a commercial search engine's shopping vertical.


Attacks on Local Searching Tools

Abstract: The Google Desktop Search is an indexing tool, currently in beta testing, designed to allow users fast, intuitive, searching for local files. The principle interface is provided through a local web server which supports an interface similar to Google.com's normal web page. Indexing of local files occurs when the system is idle, and understands a number of common file types. A optional feature is that Google Desktop can integrate a short summary of a local search results with Google.com web searches. This summary includes 30-40 character snippets of local files. We have uncovered a vulnerability that would release private local data to an unauthorized remote entity. Using two different attacks, we expose the small snippets of private local data to a remote third party.


Building Better Incentives for Robustness in BitTorrent

Abstract: BitTorrent is a widely-deployed, peer-to-peer file transfer protocol engineered with a "tit for tat" mechanism that encourages cooperation. Unfortunately, there is little incentive for nodes to altruistically provide service to their peers after they finish downloading a file, and what altruism there is can be exploited by aggressive clients like Bit- Tyrant. This altruism, called seeding, is always beneficial and sometimes essential to BitTorrent's real-world performance. We propose a new long-term incentives mechanism in BitTorrent to encourage peers to seed and we evaluate its effectiveness via simulation. We show that when nodes running our algorithm reward one another for good behavior in previous swarms, they experience as much as a 50% improvement in download times over unrewarded nodes. Even when aggressive clients, such as BitTyrant, participate in the swarm, our rewarded nodes still outperform them, although by smaller margins.


The BitTorrent Anonymity Marketplace

Abstract: The very nature of operations in peer-to-peer systems such as BitTorrent exposes information about participants to their peers. Nodes desiring anonymity, therefore, often chose to route their peer-to-peer traffic through anonymity relays, such as Tor. Unfortunately, these relays have little incentive for contribution and struggle to scale with the high loads that P2P traffic foists upon them. We propose a novel modification for BitTorrent that we call the BitTorrent Anonymity Marketplace. Peers in our system trade in k swarms obscuring the actual intent of the participants. But because peers can cross-trade torrents, the k-1 cover traffic can actually serve a useful purpose. This creates a system wherein a neighbor cannot determine if a node actually wants a given torrent, or if it is only using it as leverage to get the one it really wants. In this paper, we present our design, explore its operation in simulation, and analyze its effectiveness. We demonstrate that the upload and download characteristics of cover traffic and desired torrents are statistically difficult to distinguish.


Structured Learning of Two-Level Dynamic Rankings

Abstract: For ambiguous queries, conventional retrieval systems are bound by two conflicting goals. On the one hand, they should diversify and strive to present results for as many query intents as possible. On the other hand, they should provide depth for each intent by displaying more than a single result. Since both diversity and depth cannot be achieved simultaneously in the conventional static retrieval model, we propose a new dynamic ranking approach. Dynamic ranking models allow users to adapt the ranking through interaction, thus overcoming the constraints of presenting a one-size-fits-all static ranking. In particular, we propose a new two-level dynamic ranking model for presenting search results to the user. In this model, a user's interactions with the first-level ranking are used to infer this user's intent, so that second-level rankings can be inserted to provide more results relevant for this intent. Unlike for previous dynamic ranking models, we provide an algorithm to efficiently compute dynamic rankings with provable approximation guarantees for a large family of performance measures. We also propose the first principled algorithm for learning dynamic ranking functions from training data. In addition to the theoretical results, we provide empirical evidence demonstrating the gains in retrieval quality that our method achieves over conventional approaches.


Absoluteness of subword inequality is undecidable

Abstract: Mateescu, Salomaa, and Yu asked: is it decidable whether a given subword history assumes only non-negative values for all words over a given alphabet. In this paper, we solve this open problem by proving that this problem is undecidable even under stronger conditions than supposed originally.


Vehicular Ad Hoc and Sensor Networks; Principles and Challenges

Abstract: The rapid increase of vehicular traffic and congestion on the highways began hampering the safe and efficient movement of traffic. Consequently, year by year, we see the ascending rate of car accidents and casualties in most of the countries. Therefore, exploiting the new technologies, e.g. wireless sensor networks, is required as a solution of reduction of these saddening and reprehensible statistics. This has motivated us to propose a novel and comprehensive system to utilize Wireless Sensor Networks for vehicular networks. We coin the vehicular network employing wireless Sensor networks as Vehicular Ad Hoc and Sensor Network, or VASNET in short. The proposed VASNET is particularly for highway traffic .VASNET is a self-organizing Ad Hoc and sensor network comprised of a large number of sensor nodes. In VASNET there are two kinds of sensor nodes, some are embedded on the vehicles-vehicular nodes- and others are deployed in predetermined distances besides the highway road, known as Road Side Sensor nodes (RSS). The vehicular nodes are used to sense the velocity of the vehicle for instance. We can have some Base Stations (BS) such as Police Traffic Station, Firefighting Group and Rescue Team. The base stations may be stationary or mobile. VASNET provides capability of wireless communication between vehicular nodes and stationary nodes, to increase safety and comfort for vehicles on the highway roads. In this paper we explain main fundamentals and challenges of VASNET.


Fear: A Fuzzy-based Energy-aware Routing Protocol for Wireless Sensor Networks

Abstract: Many energy-aware routing protocols have been proposed for wireless sensor networks. Most of them are only energy savers and do not take care about energy balancing. The energy saver protocols try to decrease the energy consumption of the network as a whole; however the energy manager protocols balance the energy consumption in the network to avoid network partitioning. This means that energy saver protocols are not necessarily energy balancing and vice versa. However, the lifetime of wireless sensor network is strictly depending on energy consumption; therefore, energy management is an essential task to be considered. This paper proposes an energy aware routing protocol, named FEAR, which considers energy balancing and energy saving. It finds a fair trade-off between energy balancing and energy saving by fuzzy set concept. FEAR routing protocol is simulated and evaluated by Glomosim simulator.


Proceedings Eight Workshop on Structural Operational Semantics 2011

Abstract: This volume contains the proceedings of SOS 2011, the Eight Workshop on Structural Operational Semantics, held on the 5th of September 2011 in Aachen, Germany as an affiliated workshop of CONCUR 2011, the 22nd International Conference on Concurrency Theory. Structural operational semantics (SOS) provides a framework for giving operational semantics to programming and specification languages. A growing number of programming languages from commercial and academic spheres have been given usable semantic descriptions by means of structural operational semantics. Because of its intuitive appeal and flexibility, structural operational semantics has found considerable application in the study of the semantics of concurrent processes. It is also a viable alternative to denotational semantics in the static analysis of programs, and in proving compiler correctness. Moreover, it has found application in emerging areas of computing such as probabilistic systems and systems biology. Structural operational semantics has been successfully applied as a formal tool to establish results that hold for classes of process description languages. This has allowed for the generalization of well-known results in the field of process algebra, and for the development of a meta-theory for process calculi based on the realization that many of the results in this field only depend upon general semantic properties of language constructs. The workshop is a forum for researchers, students and practitioners interested in new developments and directions for future investigations. One of the specific goals of the workshop is to provide a meeting point for the concurrency and programming language communities. Another goal is the dissemination of the theory and practice of SOS amongst postgraduate students and young researchers worldwide.


Conscious Machines and Consciousness Oriented Programming

Abstract: In this paper, we investigate the following question: how could you write such computer programs that can work like conscious beings? The motivation behind this question is that we want to create such applications that can see the future. The aim of this paper is to provide an overall conceptual framework for this new approach to machine consciousness. So we introduce a new programming paradigm called Consciousness Oriented Programming (COP).


A First Approach on Modelling Staff Proactiveness in Retail Simulation Models

Abstract: There has been a noticeable shift in the relative composition of the industry in the developed countries in recent years; manufacturing is decreasing while the service sector is becoming more important. However, currently most simulation models for investigating service systems are still built in the same way as manufacturing simulation models, using a process-oriented world view, i.e. they model the flow of passive entities through a system. These kinds of models allow studying aspects of operational management but are not well suited for studying the dynamics that appear in service systems due to human behaviour. For these kinds of studies we require tools that allow modelling the system and entities using an object-oriented world view, where intelligent objects serve as abstract "actors" that are goal directed and can behave proactively. In our work we combine process-oriented discrete event simulation modelling and object-oriented agent based simulation modelling to investigate the impact of people management practices on retail productivity. In this paper, we reveal in a series of experiments what impact considering proactivity can have on the output accuracy of simulation models of human centric systems. The model and data we use for this investigation are based on a case study in a UK department store. We show that considering proactivity positively influences the validity of these kinds of models and therefore allows analysts to make better recommendations regarding strategies to apply people management practises.


Equilibria und weiteres Heiteres II

Abstract: We investigate several technical and conceptual questions. Our main subject is the investigation of independence as a ternary relation in the context of non-monotonic logic. In the context of probability, this investigation was started by W.Spohn et al., and then followed by J.Pearl. We look at products of function sets, and thus continue our own investigation of independence in non-monotonic logic. We show that a finite characterization of this relation in our context is impossible, and indicate how to construct all valid rules.


Fast Approximation Algorithms for Near-optimal Large-scale Network Monitoring

Abstract: We study the problem of optimal traffic prediction and monitoring in large-scale networks. Our goal is to determine which subset of K links to monitor in order to "best" predict the traffic on the remaining links in the network. We consider several optimality criteria. This can be formulated as a combinatorial optimization problem, belonging to the family of subset selection problems. Similar NP-hard problems arise in statistics, machine learning and signal processing. Some include subset selection for regression, variable selection, and sparse approximation. Exact solutions are computationally prohibitive. We present both new heuristics as well as new efficient algorithms implementing the classical greedy heuristic - commonly used to tackle such combinatorial problems. Our approach exploits connections to principal component analysis (PCA), and yields new types of performance lower bounds which do not require submodularity of the objective functions. We show that an ensemble method applied to our new randomized heuristic algorithm, often outperforms the classical greedy heuristic in practice. We evaluate our algorithms under several large-scale networks, including real life networks.


Upward Point Set Embeddability for Convex Point Sets is in $P$

Abstract: In this paper, we present a polynomial dynamic programming algorithm that tests whether a $n$-vertex directed tree $T$ has an upward planar embedding into a convex point-set $S$ of size $n$. Further, we extend our approach to the class of outerplanar digraphs. This nontrivial and surprising result implies that any given digraph can be efficiently tested for an upward planar embedding into a given convex point set.


Axiomatizing GSOS with Predicates

Abstract: In this paper, we introduce an extension of the GSOS rule format with predicates such as termination, convergence and divergence. For this format we generalize the technique proposed by Aceto, Bloom and Vaandrager for the automatic generation of ground-complete axiomatizations of bisimilarity over GSOS systems. Our procedure is implemented in a tool that receives SOS specifications as input and derives the corresponding axiomatizations automatically. This paves the way to checking strong bisimilarity over process terms by means of theorem-proving techniques.


Formal Component-Based Semantics

Abstract: One of the proposed solutions for improving the scalability of semantics of programming languages is Component-Based Semantics, introduced by Peter D. Mosses. It is expected that this framework can also be used effectively for modular meta theoretic reasoning. This paper presents a formalization of Component-Based Semantics in the theorem prover Coq. It is based on Modular SOS, a variant of SOS, and makes essential use of dependent types, while profiting from type classes. This formalization constitutes a contribution towards modular meta theoretic formalizations in theorem provers. As a small example, a modular proof of determinism of a mini-language is developed.


Regular Expression Matching and Operational Semantics

Abstract: Many programming languages and tools, ranging from grep to the Java String library, contain regular expression matchers. Rather than first translating a regular expression into a deterministic finite automaton, such implementations typically match the regular expression on the fly. Thus they can be seen as virtual machines interpreting the regular expression much as if it were a program with some non-deterministic constructs such as the Kleene star. We formalize this implementation technique for regular expression matching using operational semantics. Specifically, we derive a series of abstract machines, moving from the abstract definition of matching to increasingly realistic machines. First a continuation is added to the operational semantics to describe what remains to be matched after the current expression. Next, we represent the expression as a data structure using pointers, which enables redundant searches to be eliminated via testing for pointer equality. From there, we arrive both at Thompson's lockstep construction and a machine that performs some operations in parallel, suitable for implementation on a large number of cores, such as a GPU. We formalize the parallel machine using process algebra and report some preliminary experiments with an implementation on a graphics processor using CUDA.


On the Unification of Process Semantics: Logical Semantics

Abstract: We continue with the task of obtaining a unifying view of process semantics by considering in this case the logical characterization of the semantics. We start by considering the classic linear time-branching time spectrum developed by R.J. van Glabbeek. He provided a logical characterization of most of the semantics in his spectrum but, without following a unique pattern. In this paper, we present a uniform logical characterization of all the semantics in the enlarged spectrum. The common structure of the formulas that constitute all the corresponding logics gives us a much clearer picture of the spectrum, clarifying the relations between the different semantics, and allows us to develop generic proofs of some general properties of the semantics.


Modeling and frequency domain analysis of nonlinear compliant joints for a passive dynamic swimmer

Abstract: In this paper we present the study of the mathematical model of a real life joint used in an underwater robotic fish. Fluid-structure interaction is utterly simplified and the motion of the joint is approximated by D\"uffing's equation. We compare the quality of analytical harmonic solutions previously reported, with the input-output relation obtained via truncated Volterra series expansion. Comparisons show a trade-off between accuracy and flexibility of the methods. The methods are discussed in detail in order to facilitate reproduction of our results. The approach presented herein can be used to verify results in nonlinear resonance applications and in the design of bio-inspired compliant robots that exploit passive properties of their dynamics. We focus on the potential use of this type of joint for energy extraction from environmental sources, in this case a K\'arm\'an vortex street shed by an obstacle in a flow. Open challenges and questions are mentioned throughout the document.


Randomized Optimal Consensus of Multi-agent Systems

Abstract: In this paper, we formulate and solve a randomized optimal consensus problem for multi-agent systems with stochastically time-varying interconnection topology. The considered multi-agent system with a simple randomized iterating rule achieves an almost sure consensus meanwhile solving the optimization problem $\min_{z\in \mathds{R}^d}\ \sum_{i=1}^n f_i(z),$ in which the optimal solution set of objective function $f_i$ can only be observed by agent $i$ itself. At each time step, simply determined by a Bernoulli trial, each agent independently and randomly chooses either taking an average among its neighbor set, or projecting onto the optimal solution set of its own optimization component. Both directed and bidirectional communication graphs are studied. Connectivity conditions are proposed to guarantee an optimal consensus almost surely with proper convexity and intersection assumptions. The convergence analysis is carried out using convex analysis. We compare the randomized algorithm with the deterministic one via a numerical example. The results illustrate that a group of autonomous agents can reach an optimal opinion by each node simply making a randomized trade-off between following its neighbors or sticking to its own opinion at each time step.


Multi-agent Robust Consensus: Convergence Analysis and Application

Abstract: The paper investigates consensus problem for continuous-time multi-agent systems with time-varying communication graphs subject to process noises. Borrowing the ideas from input-to-state stability (ISS) and integral input-to-state stability (iISS), robust consensus and integral robust consensus are defined with respect to $L_\infty$ and $L_1$ norms of the disturbance functions, respectively. Sufficient and/or necessary connectivity conditions are obtained for the system to reach robust consensus or integral robust consensus, which answer the question: how much communication capacity is required for a multi-agent network to converge despite certain amount of disturbance. The $\epsilon$-convergence time is then obtained for the network as a special case of the robustness analysis. The results are based on quite general assumptions on switching graph, weights rule and noise regularity. In addition, as an illustration of the applicability of the results, distributed event-triggered coordination is studied.