Beyond Language Equivalence on Visibly Pushdown Automata

Abstract: We study (bi)simulation-like preorder/equivalence checking on the class of visibly pushdown automata and its natural subclasses visibly BPA (Basic Process Algebra) and visibly one-counter automata. We describe generic methods for proving complexity upper and lower bounds for a number of studied preorders and equivalences like simulation, completed simulation, ready simulation, 2-nested simulation preorders/equivalences and bisimulation equivalence. Our main results are that all the mentioned equivalences and preorders are EXPTIME-complete on visibly pushdown automata, PSPACE-complete on visibly one-counter automata and P-complete on visibly BPA. Our PSPACE lower bound for visibly one-counter automata improves also the previously known DP-hardness results for ordinary one-counter automata and one-counter nets. Finally, we study regularity checking problems for visibly pushdown automata and show that they can be decided in polynomial time.


Encapsulation theory: the transformation equations of absolute information hiding

Abstract: This paper describes how the maximum potential number of edges of an encapsulated graph varies as the graph is transformed, that is, as nodes are created and modified. The equations governing these changes of maximum potential number of edges caused by the transformations are derived and briefly analysed.


A Trace Based Bisimulation for the Spi Calculus

Abstract: A notion of open bisimulation is formulated for the spi calculus, an extension of the pi-calculus with cryptographic primitives. In this formulation, open bisimulation is indexed by pairs of symbolic traces, which represent the history of interactions between the environment with the pairs of processes being checked for bisimilarity. The use of symbolic traces allows for a symbolic treatment of bound input in bisimulation checking which avoids quantification over input values. Open bisimilarity is shown to be sound with respect to testing equivalence, and futher, it is shown to be an equivalence relation on processes and a congruence relation on finite processes. As far as we know, this is the first formulation of open bisimulation for the spi calculus for which the congruence result is proved.


Concept-Oriented Model and Query Language

Abstract: We describe a new approach to data modeling, called the concept-oriented model (COM), and a novel concept-oriented query language (COQL). The model is based on three principles: duality principle postulates that any element is a couple consisting of one identity and one entity, inclusion principle postulates that any element has a super-element, and order principle assumes that any element has a number of greater elements within a partially ordered set. Concept-oriented query language is based on a new data modeling construct, called concept, inclusion relation between concepts, and concept partial ordering in which greater concepts are represented by their field types. It is demonstrated how COM and COQL can be used to solve three general data modeling tasks: logical navigation, multidimensional analysis and inference. Logical navigation is based on two operations of projection and de-projection. Multidimensional analysis uses product operation for producing a cube from level concepts chosen along the chosen dimension paths. Inference is defined as a two-step procedure where input constraints are first propagated downwards using de-projection and then the constrained result is propagated upwards using projection.


An e-Infrastructure for Collaborative Research in Human Embryo Development

Abstract: Within the context of the EU Design Study Developmental Gene Expression Map, we identify a set of challenges when facilitating collaborative research on early human embryo development. These challenges bring forth requirements, for which we have identified solutions and technology. We summarise our solutions and demonstrate how they integrate to form an e-infrastructure to support collaborative research in this area of developmental biology.


A Limit Theorem in Singular Regression Problem

Abstract: In statistical problems, a set of parameterized probability distributions is used to estimate the true probability distribution. If Fisher information matrix at the true distribution is singular, then it has been left unknown what we can estimate about the true distribution from random samples. In this paper, we study a singular regression problem and prove a limit theorem which shows the relation between the singular regression problem and two birational invariants, a real log canonical threshold and a singular fluctuation. The obtained theorem has an important application to statistics, because it enables us to estimate the generalization error from the training error without any knowledge of the true probability distribution.


The Safe Lambda Calculus

Abstract: Safety is a syntactic condition of higher-order grammars that constrains occurrences of variables in the production rules according to their type-theoretic order. In this paper, we introduce the safe lambda calculus, which is obtained by transposing (and generalizing) the safety condition to the setting of the simply-typed lambda calculus. In contrast to the original definition of safety, our calculus does not constrain types (to be homogeneous). We show that in the safe lambda calculus, there is no need to rename bound variables when performing substitution, as variable capture is guaranteed not to happen. We also propose an adequate notion of beta-reduction that preserves safety. In the same vein as Schwichtenberg's 1976 characterization of the simply-typed lambda calculus, we show that the numeric functions representable in the safe lambda calculus are exactly the multivariate polynomials; thus conditional is not definable. We also give a characterization of representable word functions. We then study the complexity of deciding beta-eta equality of two safe simply-typed terms and show that this problem is PSPACE-hard. Finally we give a game-semantic analysis of safety: We show that safe terms are denoted by `P-incrementally justified strategies'. Consequently pointers in the game semantics of safe lambda-terms are only necessary from order 4 onwards.


TR01: Time-continuous Sparse Imputation

Abstract: An effective way to increase the noise robustness of automatic speech recognition is to label noisy speech features as either reliable or unreliable (missing) prior to decoding, and to replace the missing ones by clean speech estimates. We present a novel method to obtain such clean speech estimates. Unlike previous imputation frameworks which work on a frame-by-frame basis, our method focuses on exploiting information from a large time-context. Using a sliding window approach, denoised speech representations are constructed using a sparse representation of the reliable features in an overcomplete basis of fixed-length exemplar fragments. We demonstrate the potential of our approach with experiments on the AURORA-2 connected digit database.


Grammatic -- a tool for grammar definition reuse and modularity

Abstract: Grammatic is a tool for grammar definition and manipulation aimed to improve modularity and reuse of grammars and related development artifacts. It is independent from parsing technology and any other details of target system implementation. Grammatic provides a way for annotating grammars with arbitrary metadata (like associativity attributes, semantic actions or anything else). It might be used as a front-end for external tools like parser generators to make their input grammars modular and reusable. This paper describes main principles behind Grammatic and gives an overview of languages it provides and their ability to separate concerns and define reusable modules. Also it presents sketches of possible use cases for the tool.


A Faithful Semantics for Generalised Symbolic Trajectory Evaluation

Abstract: Generalised Symbolic Trajectory Evaluation (GSTE) is a high-capacity formal verification technique for hardware. GSTE uses abstraction, meaning that details of the circuit behaviour are removed from the circuit model. A semantics for GSTE can be used to predict and understand why certain circuit properties can or cannot be proven by GSTE. Several semantics have been described for GSTE. These semantics, however, are not faithful to the proving power of GSTE-algorithms, that is, the GSTE-algorithms are incomplete with respect to the semantics. The abstraction used in GSTE makes it hard to understand why a specific property can, or cannot, be proven by GSTE. The semantics mentioned above cannot help the user in doing so. The contribution of this paper is a faithful semantics for GSTE. That is, we give a simple formal theory that deems a property to be true if-and-only-if the property can be proven by a GSTE-model checker. We prove that the GSTE algorithm is sound and complete with respect to this semantics.


On some simplicial elimination schemes for chordal graphs

Abstract: We present here some results on particular elimination schemes for chordal graphs, namely we show that for any chordal graph we can construct in linear time a simplicial elimination scheme starting with a pending maximal clique attached via a minimal separator maximal (resp. minimal) under inclusion among all minimal separators.


A Density Matrix-based Algorithm for Solving Eigenvalue Problems

Abstract: A new numerical algorithm for solving the symmetric eigenvalue problem is presented. The technique deviates fundamentally from the traditional Krylov subspace iteration based techniques (Arnoldi and Lanczos algorithms) or other Davidson-Jacobi techniques, and takes its inspiration from the contour integration and density matrix representation in quantum mechanics. It will be shown that this new algorithm - named FEAST - exhibits high efficiency, robustness, accuracy and scalability on parallel architectures. Examples from electronic structure calculations of Carbon nanotubes (CNT) are presented, and numerical performances and capabilities are discussed.


Self-stabilizing Numerical Iterative Computation

Abstract: Many challenging tasks in sensor networks, including sensor calibration, ranking of nodes, monitoring, event region detection, collaborative filtering, collaborative signal processing, {\em etc.}, can be formulated as a problem of solving a linear system of equations. Several recent works propose different distributed algorithms for solving these problems, usually by using linear iterative numerical methods. The main problem with previous approaches is that once the problem inputs change during the process of computation, the computation may output unexpected results. In real life settings, sensor measurements are subject to varying environmental conditions and to measurement noise. We present a simple iterative scheme called SS-Iterative for solving systems of linear equations, and examine its properties in the self-stabilizing perspective. We analyze the behavior of the proposed scheme under changing input sequences using two different assumptions on the input: a box bound, and a probabilistic distribution. As a case study, we discuss the sensor calibration problem and provide simulation results to support the applicability of our approach.


A Statistical Approach to Performance Monitoring in Soft Real-Time Distributed Systems

Abstract: Soft real-time applications require timely delivery of messages conforming to the soft real-time constraints. Satisfying such requirements is a complex task both due to the volatile nature of distributed environments, as well as due to numerous domain-specific factors that affect message latency. Prompt detection of the root-cause of excessive message delay allows a distributed system to react accordingly. This may significantly improve compliance with the required timeliness constraints. In this work, we present a novel approach for distributed performance monitoring of soft-real time distributed systems. We propose to employ recent distributed algorithms from the statistical signal processing and learning domains, and to utilize them in a different context of online performance monitoring and root-cause analysis, for pinpointing the reasons for violation of performance requirements. Our approach is general and can be used for monitoring of any distributed system, and is not limited to the soft real-time domain. We have implemented the proposed framework in TransFab, an IBM prototype of soft real-time messaging fabric. In addition to root-cause analysis, the framework includes facilities to resolve resource allocation problems, such as memory and bandwidth deficiency. The experiments demonstrate that the system can identify and resolve latency problems in a timely fashion.


A Hybrid Multicast-Unicast Infrastructure for Efficient Publish-Subscribe in Enterprise Networks

Abstract: One of the main challenges in building a large scale publish-subscribe infrastructure in an enterprise network, is to provide the subscribers with the required information, while minimizing the consumed host and network resources. Typically, previous approaches utilize either IP multicast or point-to-point unicast for efficient dissemination of the information. In this work, we propose a novel hybrid framework, which is a combination of both multicast and unicast data dissemination. Our hybrid framework allows us to take the advantages of both multicast and unicast, while avoiding their drawbacks. We investigate several algorithms for computing the best mapping of publishers' transmissions into multicast and unicast transport. Using extensive simulations, we show that our hybrid framework reduces consumed host and network resources, outperforming traditional solutions. To insure the subscribers interests closely resemble those of real-world settings, our simulations are based on stock market data and on recorded IBM WebShpere subscriptions.


Peer-to-Peer Secure Multi-Party Numerical Computation Facing Malicious Adversaries

Abstract: We propose an efficient framework for enabling secure multi-party numerical computations in a Peer-to-Peer network. This problem arises in a range of applications such as collaborative filtering, distributed computation of trust and reputation, monitoring and other tasks, where the computing nodes is expected to preserve the privacy of their inputs while performing a joint computation of a certain function. Although there is a rich literature in the field of distributed systems security concerning secure multi-party computation, in practice it is hard to deploy those methods in very large scale Peer-to-Peer networks. In this work, we try to bridge the gap between theoretical algorithms in the security domain, and a practical Peer-to-Peer deployment. We consider two security models. The first is the semi-honest model where peers correctly follow the protocol, but try to reveal private information. We provide three possible schemes for secure multi-party numerical computation for this model and identify a single light-weight scheme which outperforms the others. Using extensive simulation results over real Internet topologies, we demonstrate that our scheme is scalable to very large networks, with up to millions of nodes. The second model we consider is the malicious peers model, where peers can behave arbitrarily, deliberately trying to affect the results of the computation as well as compromising the privacy of other peers. For this model we provide a fourth scheme to defend the execution of the computation against the malicious peers. The proposed scheme has a higher complexity relative to the semi-honest model. Overall, we provide the Peer-to-Peer network designer a set of tools to choose from, based on the desired level of security.


Language recognition by generalized quantum finite automata with unbounded error (abstract & poster)

Abstract: In this note, we generalize the results of arXiv:0901.2703v1 We show that all one-way quantum finite automaton (QFA) models that are at least as general as Kondacs-Watrous QFA's are equivalent in power to classical probabilistic finite automata in this setting. Unlike their probabilistic counterparts, allowing the tape head to stay put for some steps during its traversal of the input does enlarge the class of languages recognized by such QFA's with unbounded error. (Note that, the proof of Theorem 1 in the abstract was presented in the previous version (arXiv:0901.2703v1).)


Information science and technology as applications of the physics of signalling

Abstract: Adopting the scientific method a theoretical model is proposed as foundation for information science and technology, extending the existing theory of signaling: a fact f becomes known in a physical system only following the success of a test f, tests performed primarily by human sensors and applied to (physical) phenomena within which further tests may be performed. Tests are phenomena and classify phenomena. A phenomenon occupies both time and space, facts and inferences having physical counterparts which are phenomena of specified classes. Identifiers such as f are conventional, assigned by humans; a fact (f', f'') reports the success of a test of generic class f', the outcome f'' of the reported application classifying the successful test in more detail. Facts then exist only within structures of a form dictated by constraints on the structural design of tests. The model explains why responses of real time systems are not uniquely predictable and why restrictions, on concurrency in performing inferences within them, are needed. Improved methods, based on the model and applicable throughout the software life-cycle, are summarised in the paper. No report of similar work has been found in the literature.


A Super-Polynomial Lower Bound for the Parity Game Strategy Improvement Algorithm as We Know it

Abstract: This paper presents a new lower bound for the discrete strategy improvement algorithm for solving parity games due to Voege and Jurdziski. First, we informally show which structures are difficult to solve for the algorithm. Second, we outline a family of games of quadratic size on which the algorithm requires exponentially many strategy iterations, answering in the negative the long-standing question whether this algorithm runs in polynomial time. Additionally we note that the same family of games can be used to prove a similar result w.r.t. the strategy improvement variant by Schewe.


Automatic Analog Beamforming Transceiver for 60 GHz Radios

Abstract: We propose a transceiver architecture for automatic beamforming and instantaneous setup of a multigigabit-per-second wireless link between two millimeter wave radios. The retro-directive architecture eliminates necessity of slow and complex digital algorithms required for searching and tracking the directions of opposite end radios. Simulations predict <5 micro-seconds setup time for a 2-Gbps bidirectional 60-GHz communication link between two 10-meters apart radios. The radios have 4-element arrayed antennas, and use QPSK modulation with 1.5 GHz analog bandwidth.


On finitely recursive programs

Abstract: Disjunctive finitary programs are a class of logic programs admitting function symbols and hence infinite domains. They have very good computational properties, for example ground queries are decidable while in the general case the stable model semantics is highly undecidable. In this paper we prove that a larger class of programs, called finitely recursive programs, preserves most of the good properties of finitary programs under the stable model semantics, namely: (i) finitely recursive programs enjoy a compactness property; (ii) inconsistency checking and skeptical reasoning are semidecidable; (iii) skeptical resolution is complete for normal finitely recursive programs. Moreover, we show how to check inconsistency and answer skeptical queries using finite subsets of the ground program instantiation. We achieve this by extending the splitting sequence theorem by Lifschitz and Turner: We prove that if the input program P is finitely recursive, then the partial stable models determined by any smooth splitting omega-sequence converge to a stable model of P.


Online validation of the pi and pi' failure functions

Abstract: Let pi_w denote the failure function of the Morris-Pratt algorithm for a word w. In this paper we study the following problem: given an integer array A[1..n], is there a word w over arbitrary alphabet such that A[i]=pi_w[i] for all i? Moreover, what is the minimum required cardinality of the alphabet? We give a real time linear algorithm for this problem in the unit-cost RAM model with \Theta(log n) bits word size. Our algorithm returns a word w over minimal alphabet such that pi_w = A as well and uses just o(n) words of memory. Then we consider function pi' instead of pi and give an online O(n log n) algorithm for this case. This is the first polynomial algorithm for online version of this problem.


An O(log(n)) Fully Dynamic Algorithm for Maximum matching in a tree

Abstract: In this paper, we have developed a fully-dynamic algorithm for maintaining cardinality of maximum-matching in a tree using the construction of top-trees. The time complexities are as follows: 1. Initialization Time: $O(n(log(n)))$ to build the Top-tree. 2. Update Time: $O(log(n))$ 3. Query Time: O(1) to query the cardinality of maximum-matching and $O(log(n))$ to find if a particular edge is matched.


Measuring communication complexity using instance complexity with oracles

Abstract: We establish a connection between non-deterministic communication complexity and instance complexity, a measure of information based on algorithmic entropy. Let $\overline{x}$, $\overline{y}$ and $Y_1(\overline{x})$ be respectively the input known by Alice, the input known by Bob, and the set of all values of $y$ such that $f(\overline{x},y)=1$; a string is a witness of the non-deterministic communication protocol iff it is a program $p$ that "corresponds exactly" to the instance complexity $\ic^{f,t}(\overline{y}:Y_1(\overline{x}))$.


An Algebraic Watchdog for Wireless Network Coding

Abstract: In this paper, we propose a scheme, called the "algebraic watchdog" for wireless network coding, in which nodes can detect malicious behaviors probabilistically, police their downstream neighbors locally using overheard messages, and, thus, provide a secure global "self-checking network". Unlike traditional Byzantine detection protocols which are receiver-based, this protocol gives the senders an active role in checking the node downstream. This work is inspired by Marti et. al.'s watchdog-pathrater, which attempts to detect and mitigate the effects of routing misbehavior. As the first building block of a such system, we focus on a two-hop network. We present a graphical model to understand the inference process nodes execute to police their downstream neighbors; as well as to compute, analyze, and approximate the probabilities of misdetection and false detection. In addition, we present an algebraic analysis of the performance using an hypothesis testing framework, that provides exact formulae for probabilities of false detection and misdetection.


Statistical analysis of the Indus script using $n$-grams

Abstract: The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilisation. Recently, some researchers have questioned the premise that the Indus script encodes spoken language. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically $n$-gram Markov chains, to analyse the Indus script for syntax. Our main results are that the script has well-defined signs which begin and end texts, that there is directionality and strong correlations in the sign order, and that there are groups of signs which appear to have identical syntactic function. All these require no {\it a priori} suppositions regarding the syntactic or semantic content of the signs, but follow directly from the statistical analysis. Using information theoretic measures, we find the information in the script to be intermediate between that of a completely random and a completely fixed ordering of signs. Our study reveals that the Indus script is a structured sign system showing features of a formal language, but, at present, cannot conclusively establish that it encodes {\it natural} language. Our $n$-gram Markov model is useful for predicting signs which are missing or illegible in a corpus of Indus texts. This work forms the basis for the development of a stochastic grammar which can be used to explore the syntax of the Indus script in greater detail.


Average number of flips in pancake sorting

Abstract: We are given a stack of pancakes of different sizes and the only allowed operation is to take several pancakes from top and flip them. The unburnt version requires the pancakes to be sorted by their sizes at the end, while in the burnt version they additionally need to be oriented burnt-side down. We present an algorithm with the average number of flips, needed to sort a stack of n burnt pancakes, equal to 7n/4+O(1) and a randomized algorithm for the unburnt version with at most 17n/12+O(1) flips on average. In addition, we show that in the burnt version, the average number of flips of any algorithm is at least n+\Omega(n/log n) and conjecture that some algorithm can reach n+\Theta(n/log n). We also slightly increase the lower bound on g(n), the minimum number of flips needed to sort the worst stack of n burnt pancakes. This bound, together with the upper bound found by Heydari and Sudborough in 1997, gives the exact number of flips to sort the previously conjectured worst stack -I_n for n=3 mod 4 and n>=15. Finally we present exact values of f(n) up to n=19 and of g(n) up to n=17 and disprove a conjecture of Cohen and Blum by showing that the burnt stack -I_{15} is not the worst one for n=15.


Self-assembly of the discrete Sierpinski carpet and related fractals

Abstract: It is well known that the discrete Sierpinski triangle can be defined as the nonzero residues modulo 2 of Pascal's triangle, and that from this definition one can easily construct a tileset with which the discrete Sierpinski triangle self-assembles in Winfree's tile assembly model. In this paper we introduce an infinite class of discrete self-similar fractals that are defined by the residues modulo a prime p of the entries in a two-dimensional matrix obtained from a simple recursive equation. We prove that every fractal in this class self-assembles using a uniformly constructed tileset. As a special case we show that the discrete Sierpinski carpet self-assembles using a set of 30 tiles.


A Distributed Trust Diffusion Protocol for Ad Hoc Networks

Abstract: In this paper, we propose and evaluate a distributed protocol to manage trust diffusion in ad hoc networks. In this protocol, each node i maintains a \trust value" about an other node j which is computed both as a result of the exchanges with node j itself and as a function of the opinion that other nodes have about j. These two aspects are respectively weighted by a trust index that measures the trust quality the node has in its own experiences and by a trust index representing the trust the node has in the opinions of the other nodes. Simulations have been realized to validate the robustness of this protocol against three kinds of attacks: simple coalitions, Trojan attacks and detonator attacks.


On Leveraging Partial Paths in Partially-Connected Networks

Abstract: Mobile wireless network research focuses on scenarios at the extremes of the network connectivity continuum where the probability of all nodes being connected is either close to unity, assuming connected paths between all nodes (mobile ad hoc networks), or it is close to zero, assuming no multi-hop paths exist at all (delay-tolerant networks). In this paper, we argue that a sizable fraction of networks lies between these extremes and is characterized by the existence of partial paths, i.e. multi-hop path segments that allow forwarding data closer to the destination even when no end-to-end path is available. A fundamental issue in such networks is dealing with disruptions of end-to-end paths. Under a stochastic model, we compare the performance of the established end-to-end retransmission (ignoring partial paths), against a forwarding mechanism that leverages partial paths to forward data closer to the destination even during disruption periods. Perhaps surprisingly, the alternative mechanism is not necessarily superior. However, under a stochastic monotonicity condition between current v.s. future path length, which we demonstrate to hold in typical network models, we manage to prove superiority of the alternative mechanism in stochastic dominance terms. We believe that this study could serve as a foundation to design more efficient data transfer protocols for partially-connected networks, which could potentially help reducing the gap between applications that can be supported over disconnected networks and those requiring full connectivity.


Computing Rooted and Unrooted Maximum Consistent Supertrees

Abstract: A chief problem in phylogenetics and database theory is the computation of a maximum consistent tree from a set of rooted or unrooted trees. A standard input are triplets, rooted binary trees on three leaves, or quartets, unrooted binary trees on four leaves. We give exact algorithms constructing rooted and unrooted maximum consistent supertrees in time O(2^n n^5 m^2 log(m)) for a set of m triplets (quartets), each one distinctly leaf-labeled by some subset of n labels. The algorithms extend to weighted triplets (quartets). We further present fast exact algorithms for constructing rooted and unrooted maximum consistent trees in polynomial space. Finally, for a set T of m rooted or unrooted trees with maximum degree D and distinctly leaf-labeled by some subset of a set L of n labels, we compute, in O(2^{mD} n^m m^5 n^6 log(m)) time, a tree distinctly leaf-labeled by a maximum-size subset X of L that all trees in T, when restricted to X, are consistent with.


Nuclear norm minimization for the planted clique and biclique problems

Abstract: We consider the problems of finding a maximum clique in a graph and finding a maximum-edge biclique in a bipartite graph. Both problems are NP-hard. We write both problems as matrix-rank minimization and then relax them using the nuclear norm. This technique, which may be regarded as a generalization of compressive sensing, has recently been shown to be an effective way to solve rank optimization problems. In the special cases that the input graph has a planted clique or biclique (i.e., a single large clique or biclique plus diversionary edges), our algorithm successfully provides an exact solution to the original instance. For each problem, we provide two analyses of when our algorithm succeeds. In the first analysis, the diversionary edges are placed by an adversary. In the second, they are placed at random. In the case of random edges for the planted clique problem, we obtain the same bound as Alon, Krivelevich and Sudakov as well as Feige and Krauthgamer, but we use different techniques.


A Boundary Approximation Algorithm for Distributed Sensor Networks

Abstract: We present an algorithm for boundary approximation in locally-linked sensor networks that communicate with a remote monitoring station. Delaunay triangulations and Voronoi diagrams are used to generate a sensor communication network and define boundary segments between sensors, respectively. The proposed algorithm reduces remote station communication by approximating boundaries via a decentralized computation executed within the sensor network. Moreover, the algorithm identifies boundaries based on differences between neighboring sensor readings, and not absolute sensor values. An analysis of the bandwidth consumption of the algorithm is presented and compared to two naive approaches. The proposed algorithm reduces the amount of remote communication (compared to the naive approaches) and becomes increasingly useful in networks with more nodes.


Code injection attacks on harvard-architecture devices

Abstract: Harvard architecture CPU design is common in the embedded world. Examples of Harvard-based architecture devices are the Mica family of wireless sensors. Mica motes have limited memory and can process only very small packets. Stack-based buffer overflow techniques that inject code into the stack and then execute it are therefore not applicable. It has been a common belief that code injection is impossible on Harvard architectures. This paper presents a remote code injection attack for Mica sensors. We show how to exploit program vulnerabilities to permanently inject any piece of code into the program memory of an Atmel AVR-based sensor. To our knowledge, this is the first result that presents a code injection technique for such devices. Previous work only succeeded in injecting data or performing transient attacks. Injecting permanent code is more powerful since the attacker can gain full control of the target sensor. We also show that this attack can be used to inject a worm that can propagate through the wireless sensor network and possibly create a sensor botnet. Our attack combines different techniques such as return oriented programming and fake stack injection. We present implementation details and suggest some counter-measures.


Automating Access Control Logics in Simple Type Theory with LEO-II

Abstract: Garg and Abadi recently proved that prominent access control logics can be translated in a sound and complete way into modal logic S4. We have previously outlined how normal multimodal logics, including monomodal logics K and S4, can be embedded in simple type theory (which is also known as higher-order logic) and we have demonstrated that the higher-order theorem prover LEO-II can automate reasoning in and about them. In this paper we combine these results and describe a sound and complete embedding of different access control logics in simple type theory. Employing this framework we show that the off the shelf theorem prover LEO-II can be applied to automate reasoning in prominent access control logics.


Resource Adaptive Agents in Interactive Theorem Proving

Abstract: We introduce a resource adaptive agent mechanism which supports the user in interactive theorem proving. The mechanism uses a two layered architecture of agent societies to suggest appropriate commands together with possible command argument instantiations. Experiments with this approach show that its effectiveness can be further improved by introducing a resource concept. In this paper we provide an abstract view on the overall mechanism, motivate the necessity of an appropriate resource concept and discuss its realization within the agent architecture.


On the Dual Formulation of Boosting Algorithms

Abstract: We study boosting algorithms from a new perspective. We show that the Lagrange dual problems of AdaBoost, LogitBoost and soft-margin LPBoost with generalized hinge loss are all entropy maximization problems. By looking at the dual problems of these boosting algorithms, we show that the success of boosting algorithms can be understood in terms of maintaining a better margin distribution by maximizing margins and at the same time controlling the margin variance.We also theoretically prove that, approximately, AdaBoost maximizes the average margin, instead of the minimum margin. The duality formulation also enables us to develop column generation based optimization algorithms, which are totally corrective. We show that they exhibit almost identical classification results to that of standard stage-wise additive boosting algorithms but with much faster convergence rates. Therefore fewer weak classifiers are needed to build the ensemble using our proposed optimization technique.


A remark on higher order RUE-resolution with EXTRUE

Abstract: We show that a prominent counterexample for the completeness of first order RUE-resolution does not apply to the higher order RUE-resolution approach EXTRUE.


Safe Carrier Sensing Range in CSMA Network under Physical Interference Model

Abstract: In this paper, we study the setting of carrier-sensing range in 802.11 networks under the (cumulative) physical interference model. Specifically, we identify a carrier-sensing range that will prevent collisions in 802.11 networks due to carrier-sensing failure under the physical interference model. We find that the carrier-sensing range required under the physical interference model must be larger than that required under the protocol (pairwise) interference model by a multiplicative factor. For example, if the SINR requirement is 10dB and the path-loss exponent is 4, the factor is 1.4. Furthermore, given a fixed pathloss exponent of 4, the factor increases as the SINR requirement increases. However, the limit of the factor is 1.84 as the SINR requirement goes to infinity.


A Constructive Generalization of Nash Equilibrium

Abstract: In a society of multiple individuals, if everybody is only interested in maximizing his own payoff, will there exist any equilibrium for the society? John Nash proved more than 50 years ago that an equilibrium always exists such that nobody would benefit from unilaterally changing his strategy. Nash Equilibrium is a central concept in game theory, which offers the mathematical foundation for social science and economy. However, the original definition is declarative without including a solution to find them. It has been found later that it is computationally difficult to find a Nash equilibrium. Furthermore, a Nash equilibrium may be unstable, sensitive to the smallest variation of payoff functions. Making the situation worse, a society with selfish individuals can have an enormous number of equilibria, making it extremely hard to find out the global optimal one. This paper offers a constructive generalization of Nash equilibrium to cover the case when the selfishness of individuals are reduced to lower levels in a controllable way. It shows that the society has one and only one equilibrium when the selfishness is reduced to a certain level. When every individual follows the iterative, soft-decision optimization process presented in this paper, the society converges to the unique equilibrium with an exponential rate under any initial conditions. When it is a consensus equilibrium at the same time, it must be the global optimum. The study of this paper suggests that, to build a good, stable society (including the financial market) for the benefit everyone in it, the pursuing of maximal payoff by each individual should be controlled at some level either by voluntary good citizenship or some proper regulations.


Mechanized semantics for the Clight subset of the C language

Abstract: This article presents the formal semantics of a large subset of the C language called Clight. Clight includes pointer arithmetic, "struct" and "union" types, C loops and structured "switch" statements. Clight is the source language of the CompCert verified compiler. The formal semantics of Clight is a big-step operational semantics that observes both terminating and diverging executions and produces traces of input/output events. The formal semantics of Clight is mechanized using the Coq proof assistant. In addition to the semantics of Clight, this article describes its integration in the CompCert verified compiler and several ways by which the semantics was validated.


Enterprise model verification and validation: an approach

Abstract: This article presents a Verification and Validation approach which is used here in order to complete the classical tool box the industrial user may utilize in Enterprise Modeling and Integration domain. This approach, which has been defined independently from any application domain is based on several formal concepts and tools presented in this paper. These concepts are property concepts, property reference matrix, properties graphs, enterprise modeling domain ontology, conceptual graphs and formal reasoning mechanisms.


Homotopy methods for multiplication modulo triangular sets

Abstract: We study the cost of multiplication modulo triangular families of polynomials. Following previous work by Li, Moreno Maza and Schost, we propose an algorithm that relies on homotopy and fast evaluation-interpolation techniques. We obtain a quasi-linear time complexity for substantial families of examples, for which no such result was known before. Applications are given to notably addition of algebraic numbers in small characteristic.


The Complexity of Computing Minimal Unidirectional Covering Sets

Abstract: Given a binary dominance relation on a set of alternatives, a common thread in the social sciences is to identify subsets of alternatives that satisfy certain notions of stability. Examples can be found in areas as diverse as voting theory, game theory, and argumentation theory. Brandt and Fischer [BF08] proved that it is NP-hard to decide whether an alternative is contained in some inclusion-minimal upward or downward covering set. For both problems, we raise this lower bound to the Theta_{2}^{p} level of the polynomial hierarchy and provide a Sigma_{2}^{p} upper bound. Relatedly, we show that a variety of other natural problems regarding minimal or minimum-size covering sets are hard or complete for either of NP, coNP, and Theta_{2}^{p}. An important consequence of our results is that neither minimal upward nor minimal downward covering sets (even when guaranteed to exist) can be computed in polynomial time unless P=NP. This sharply contrasts with Brandt and Fischer's result that minimal bidirectional covering sets (i.e., sets that are both minimal upward and minimal downward covering sets) are polynomial-time computable.


Randomly colouring simple hypergraphs

Abstract: We study the problem of constructing a (near) random proper $q$-colouring of a simple k-uniform hypergraph with n vertices and maximum degree \Delta. (Proper in that no edge is mono-coloured and simple in that two edges have maximum intersection of size one). We give conditions on q,\Delta so that if these conditions are satisfied, Glauber dynamics will converge in O(n\log n) time from a random (improper) start. The interesting thing here is that for k\geq 3 we can take q=o(\D).


Sorting improves word-aligned bitmap indexes

Abstract: Bitmap indexes must be compressed to reduce input/output costs and minimize CPU usage. To accelerate logical operations (AND, OR, XOR) over bitmaps, we use techniques based on run-length encoding (RLE), such as Word-Aligned Hybrid (WAH) compression. These techniques are sensitive to the order of the rows: a simple lexicographical sort can divide the index size by 9 and make indexes several times faster. We investigate row-reordering heuristics. Simply permuting the columns of the table can increase the sorting efficiency by 40%. Secondary contributions include efficient algorithms to construct and aggregate bitmaps. The effect of word length is also reviewed by constructing 16-bit, 32-bit and 64-bit indexes. Using 64-bit CPUs, we find that 64-bit indexes are slightly faster than 32-bit indexes despite being nearly twice as large.


Bid Optimization in Broad-Match Ad auctions

Abstract: Ad auctions in sponsored search support ``broad match'' that allows an advertiser to target a large number of queries while bidding only on a limited number. While giving more expressiveness to advertisers, this feature makes it challenging to optimize bids to maximize their returns: choosing to bid on a query as a broad match because it provides high profit results in one bidding for related queries which may yield low or even negative profits. We abstract and study the complexity of the {\em bid optimization problem} which is to determine an advertiser's bids on a subset of keywords (possibly using broad match) so that her profit is maximized. In the query language model when the advertiser is allowed to bid on all queries as broad match, we present an linear programming (LP)-based polynomial-time algorithm that gets the optimal profit. In the model in which an advertiser can only bid on keywords, ie., a subset of keywords as an exact or broad match, we show that this problem is not approximable within any reasonable approximation factor unless P=NP. To deal with this hardness result, we present a constant-factor approximation when the optimal profit significantly exceeds the cost. This algorithm is based on rounding a natural LP formulation of the problem. Finally, we study a budgeted variant of the problem, and show that in the query language model, one can find two budget constrained ad campaigns in polynomial time that implement the optimal bidding strategy. Our results are the first to address bid optimization under the broad match feature which is common in ad auctions.


Closures in Formal Languages and Kuratowski's Theorem

Abstract: A famous theorem of Kuratowski states that in a topological space, at most 14 distinct sets can be produced by repeatedly applying the operations of closure and complement to a given set. We re-examine this theorem in the setting of formal languages, where closure is either Kleene closure or positive closure. We classify languages according to the structure of the algebra they generate under iterations of complement and closure. We show that there are precisely 9 such algebras in the case of positive closure, and 12 in the case of Kleene closure.


Closures in Formal Languages: Concatenation, Separation, and Algorithms

Abstract: We continue our study of open and closed languages. We investigate how the properties of being open and closed are preserved under concatenation. We investigate analogues, in formal languages, of the separation axioms in topological spaces; one of our main results is that there is a clopen partition separating two words if and only if the words commute. We show that we can decide in quadratic time if the language specified by a DFA is closed, but if the language is specified by an NFA, the problem is PSPACE-complete.


Deceptiveness and Neutrality - the ND family of fitness landscapes

Abstract: When a considerable number of mutations have no effects on fitness values, the fitness landscape is said neutral. In order to study the interplay between neutrality, which exists in many real-world applications, and performances of metaheuristics, it is useful to design landscapes which make it possible to tune precisely neutral degree distribution. Even though many neutral landscape models have already been designed, none of them are general enough to create landscapes with specific neutral degree distributions. We propose three steps to design such landscapes: first using an algorithm we construct a landscape whose distribution roughly fits the target one, then we use a simulated annealing heuristic to bring closer the two distributions and finally we affect fitness values to each neutral network. Then using this new family of fitness landscapes we are able to highlight the interplay between deceptiveness and neutrality.


Fast algorithms for differential equations in positive characteristic

Abstract: We address complexity issues for linear differential equations in characteristic $p>0$: resolution and computation of the $p$-curvature. For these tasks, our main focus is on algorithms whose complexity behaves well with respect to $p$. We prove bounds linear in $p$ on the degree of polynomial solutions and propose algorithms for testing the existence of polynomial solutions in sublinear time $\tilde{O}(p^{1/2})$, and for determining a whole basis of the solution space in quasi-linear time $\tilde{O}(p)$; the $\tilde{O}$ notation indicates that we hide logarithmic factors. We show that for equations of arbitrary order, the $p$-curvature can be computed in subquadratic time $\tilde{O}(p^{1.79})$, and that this can be improved to $O(\log(p))$ for first order equations and to $\tilde{O}(p)$ for classes of second order equations.


Graph-based local elimination algorithms in discrete optimization

Abstract: The aim of this paper is to provide a review of structural decomposition methods in discrete optimization and to give a unified framework in the form of local elimination algorithms (LEA). This paper is organized as follows. Local elimination algorithms for discrete optimization (DO) problems (DOPs) with constraints are considered; a classification of dynamic programming computational procedures is given. We introduce Elimination Game and Elimination tree. Application of bucket elimination algorithm from constraint satisfaction (CS) to solving DOPs is done. We consider different local elimination schemes and related notions. Clustering that merges several variables into single meta-variable defines a promising approach to solve DOPs. This allows to create a quotient (condensed) graph and apply a local block elimination algorithm. In order to describe a block elimination process, we introduce Block Elimination Game. We discuss the connection of aforementioned local elimination algorithmic schemes and a way of transforming the directed acyclic graph (DAG) of computational LEA procedure to the tree decomposition.


iKlax: a New Musical Audio Format for Active Listening

Abstract: In this paper, we are presenting a new model for interactive music. Unlike most interactive systems, our model is based on file organization, but does not require digital audio treatments. This model includes a definition of a constraints system and its solver. The products of this project are intended for the general public, inexperienced users, as well as professional musicians, and will be distributed commercially. We are here presenting three products of this project. The difficulty of this project is to design a technology and software products for interactive music which must be easy to use by the general public and by professional composers.


A Program Transformation for Continuation Call-Based Tabled Execution

Abstract: The advantages of tabled evaluation regarding program termination and reduction of complexity are well known --as are the significant implementation, portability, and maintenance efforts that some proposals (especially those based on suspension) require. This implementation effort is reduced by program transformation-based continuation call techniques, at some efficiency cost. However, the traditional formulation of this proposal by Ramesh and Cheng limits the interleaving of tabled and non-tabled predicates and thus cannot be used as-is for arbitrary programs. In this paper we present a complete translation for the continuation call technique which, using the runtime support needed for the traditional proposal, solves these problems and makes it possible to execute arbitrary tabled programs. We present performance results which show that CCall offers a useful tradeoff that can be competitive with state-of-the-art implementations.


Model-Based Event Detection in Wireless Sensor Networks

Abstract: In this paper we present an application of techniques from statistical signal processing to the problem of event detection in wireless sensor networks used for environmental monitoring. The proposed approach uses the well-established Principal Component Analysis (PCA) technique to build a compact model of the observed phenomena that is able to capture daily and seasonal trends in the collected measurements. We then use the divergence between actual measurements and model predictions to detect the existence of discrete events within the collected data streams. Our preliminary results show that this event detection mechanism is sensitive enough to detect the onset of rain events using the temperature modality of a wireless sensor network.


Area-Universal Rectangular Layouts

Abstract: A rectangular layout is a partition of a rectangle into a finite set of interior-disjoint rectangles. Rectangular layouts appear in various applications: as rectangular cartograms in cartography, as floorplans in building architecture and VLSI design, and as graph drawings. Often areas are associated with the rectangles of a rectangular layout and it might hence be desirable if one rectangular layout can represent several area assignments. A layout is area-universal if any assignment of areas to rectangles can be realized by a combinatorially equivalent rectangular layout. We identify a simple necessary and sufficient condition for a rectangular layout to be area-universal: a rectangular layout is area-universal if and only if it is one-sided. More generally, given any rectangular layout L and any assignment of areas to its regions, we show that there can be at most one layout (up to horizontal and vertical scaling) which is combinatorially equivalent to L and achieves a given area assignment. We also investigate similar questions for perimeter assignments. The adjacency requirements for the rectangles of a rectangular layout can be specified in various ways, most commonly via the dual graph of the layout. We show how to find an area-universal layout for a given set of adjacency requirements whenever such a layout exists.


Revisiting the Age of Enlightenment from a Collective Decision Making Systems Perspective

Abstract: The ideals of the eighteenth century's Age of Enlightenment are the foundation of modern democracies. The era was characterized by thinkers who promoted progressive social reforms that opposed the long-established aristocracies and monarchies of the time. Prominent examples of such reforms include the establishment of inalienable human rights, self-governing republics, and market capitalism. Twenty-first century democratic nations can benefit from revisiting the systems developed during the Enlightenment and reframing them within the techno-social context of the Information Age. This article explores the application of social algorithms that make use of Thomas Paine's (English: 1737--1809) representatives, Adam Smith's (Scottish: 1723--1790) self-interested actors, and Marquis de Condorcet's (French: 1743--1794) optimal decision making groups. It is posited that technology-enabled social algorithms can better realize the ideals articulated during the Enlightenment.


Effectively Searching Maps in Web Documents

Abstract: Maps are an important source of information in archaeology and other sciences. Users want to search for historical maps to determine recorded history of the political geography of regions at different eras, to find out where exactly archaeological artifacts were discovered, etc. Currently, they have to use a generic search engine and add the term map along with other keywords to search for maps. This crude method will generate a significant number of false positives that the user will need to cull through to get the desired results. To reduce their manual effort, we propose an automatic map identification, indexing, and retrieval system that enables users to search and retrieve maps appearing in a large corpus of digital documents using simple keyword queries. We identify features that can help in distinguishing maps from other figures in digital documents and show how a Support-Vector-Machine-based classifier can be used to identify maps. We propose map-level-metadata e.g., captions, references to the maps in text, etc. and document-level metadata, e.g., title, abstract, citations, how recent the publication is, etc. and show how they can be automatically extracted and indexed. Our novel ranking algorithm weights different metadata fields differently and also uses the document-level metadata to help rank retrieved maps. Empirical evaluations show which features should be selected and which metadata fields should be weighted more. We also demonstrate improved retrieval results in comparison to adaptations of existing methods for map retrieval. Our map search engine has been deployed in an online map-search system that is part of the Blind-Review digital library system.


Stop the Chase

Abstract: The chase procedure, an algorithm proposed 25+ years ago to fix constraint violations in database instances, has been successfully applied in a variety of contexts, such as query optimization, data exchange, and data integration. Its practicability, however, is limited by the fact that - for an arbitrary set of constraints - it might not terminate; even worse, chase termination is an undecidable problem in general. In response, the database community has proposed sufficient restrictions on top of the constraints that guarantee chase termination on any database instance. In this paper, we propose a novel sufficient termination condition, called inductive restriction, which strictly generalizes previous conditions, but can be checked as efficiently. Furthermore, we motivate and study the problem of data-dependent chase termination and, as a key result, present sufficient termination conditions w.r.t. fixed instances. They are strictly more general than inductive restriction and might guarantee termination although the chase does not terminate in the general case.


Du corpus au dictionnaire

Abstract: In this article, we propose an automatic process to build multi-lingual lexico-semantic resources. The goal of these resources is to browse semantically textual information contained in texts of different languages. This method uses a mathematical model called Atlas s\'emantiques in order to represent the different senses of each word. It uses the linguistic relations between words to create graphs that are projected into a semantic space. These projections constitute semantic maps that denote the sense trends of each given word. This model is fed with syntactic relations between words extracted from a corpus. Therefore, the lexico-semantic resource produced describes all the words and all their meanings observed in the corpus. The sense trends are expressed by syntactic contexts, typical for a given meaning. The link between each sense trend and the utterances used to build the sense trend are also stored in an index. Thus all the instances of a word in a particular sense are linked and can be browsed easily. And by using several corpora of different languages, several resources are built that correspond with each other through languages. It makes it possible to browse information through languages thanks to syntactic contexts translations (even if some of them are partial).


Max Edge Coloring of Trees

Abstract: We study the weighted generalization of the edge coloring problem where the weight of each color class (matching) equals to the weight of its heaviest edge and the goal is to minimize the sum of the colors' weights. We present a 3/2-approximation algorithm for trees.


Mining for adverse drug events with formal concept analysis

Abstract: The pharmacovigilance databases consist of several case reports involving drugs and adverse events (AEs). Some methods are applied consistently to highlight all signals, i.e. all statistically significant associations between a drug and an AE. These methods are appropriate for verification of more complex relationships involving one or several drug(s) and AE(s) (e.g; syndromes or interactions) but do not address the identification of them. We propose a method for the extraction of these relationships based on Formal Concept Analysis (FCA) associated with disproportionality measures. This method identifies all sets of drugs and AEs which are potential signals, syndromes or interactions. Compared to a previous experience of disproportionality analysis without FCA, the addition of FCA was more efficient for identifying false positives related to concomitant drugs.


Cross-situational and supervised learning in the emergence of communication

Abstract: Scenarios for the emergence or bootstrap of a lexicon involve the repeated interaction between at least two agents who must reach a consensus on how to name N objects using H words. Here we consider minimal models of two types of learning algorithms: cross-situational learning, in which the individuals determine the meaning of a word by looking for something in common across all observed uses of that word, and supervised operant conditioning learning, in which there is strong feedback between individuals about the intended meaning of the words. Despite the stark differences between these learning schemes, we show that they yield the same communication accuracy in the realistic limits of large N and H, which coincides with the result of the classical occupancy problem of randomly assigning N objects to H words.


A Proposal for Proquints: Identifiers that are Readable, Spellable, and Pronounceable

Abstract: Identifiers (IDs) are pervasive throughout our modern life. We suggest that these IDs would be easier to manage and remember if they were easily readable, spellable, and pronounceable. As a solution to this problem we propose using PRO-nouncable QUINT-uplets of alternating unambiguous consonants and vowels: _proquints_.


Using Kolmogorov Complexity for Understanding Some Limitations on Steganography

Abstract: Recently perfectly secure steganographic systems have been described for a wide class of sources of covertexts. The speed of transmission of secret information for these stegosystems is proportional to the length of the covertext. In this work we show that there are sources of covertexts for which such stegosystems do not exist. The key observation is that if the set of possible covertexts has a maximal Kolmogorov complexity, then a high-speed perfect stegosystem has to have complexity of the same order.


A Framework to Handle Linear Temporal Properties in (\omega-)Regular Model Checking

Abstract: Since the topic emerged several years ago, work on regular model checking has mostly been devoted to the verification of state reachability and safety properties. Though it was known that linear temporal properties could also be checked within this framework, little has been done about working out the corresponding details. This paper addresses this issue in the context of regular model checking based on the encoding of states by finite or infinite words. It works out the exact constructions to be used in both cases, and proposes a partial solution to the problem resulting from the fact that infinite computations of unbounded configurations might never contain the same configuration twice, thus making cycle detection problematic.


Adaptive FPGA NoC-based Architecture for Multispectral Image Correlation

Abstract: An adaptive FPGA architecture based on the NoC (Network-on-Chip) approach is used for the multispectral image correlation. This architecture must contain several distance algorithms depending on the characteristics of spectral images and the precision of the authentication. The analysis of distance algorithms is required which bases on the algorithmic complexity, result precision, execution time and the adaptability of the implementation. This paper presents the comparison of these distance computation algorithms on one spectral database. The result of a RGB algorithm implementation was discussed.


Google distance between words

Abstract: Cilibrasi and Vitanyi have demonstrated that it is possible to extract the meaning of words from the world-wide web. To achieve this, they rely on the number of webpages that are found through a Google search containing a given word and they associate the page count to the probability that the word appears on a webpage. Thus, conditional probabilities allow them to correlate one word with another word's meaning. Furthermore, they have developed a similarity distance function that gauges how closely related a pair of words is. We present a specific counterexample to the triangle inequality for this similarity distance function.


Peer to Peer Optimistic Collaborative Editing on XML-like trees

Abstract: Collaborative editing consists in editing a common document shared by several independent sites. This may give rise to conficts when two different users perform simultaneous uncompatible operations. Centralized systems solve this problem by using locks that prevent some modifications to occur and leave the resolution of confict to users. On the contrary, peer to peer (P2P) editing doesn't allow locks and the optimistic approach uses a Integration Transformation IT that reconciliates the conficting operations and ensures convergence (all copies are identical on each site). Two properties TP1 and TP2, relating the set of allowed operations Op and the transformation IT, have been shown to ensure the correctness of the process. The choice of the set Op is crucial to define an integration operation that satisfies TP1 and TP2. Many existing algorithms don't satisfy these properties and are indeed incorrect i.e. convergence is not guaranteed. No algorithm enjoying both properties is known for strings and little work has been done for XML trees in a pure P2P framework (that doesn't use time-stamps for instance). We focus on editing unranked unordered labeled trees, so-called XML-like trees that are considered for instance in the Harmony pro ject. We show that no transformation satisfying TP1 and TP2 can exist for a first set of operations but we show that TP1 and TP2 hold for a richer set of operations. We show how to combine our approach with any convergent editing process on strings (not necessarily based on integration transformation) to get a convergent process.


Geospatial semantics: beyond ontologies, towards an enactive approach

Abstract: Current approaches to semantics in the geospatial domain are mainly based on ontologies, but ontologies, since continue to build entirely on the symbolic methodology, suffers from the classical problems, e.g. the symbol grounding problem, affecting representational theories. We claim for an enactive approach to semantics, where meaning is considered to be an emergent feature arising context-dependently in action. Since representational theories are unable to deal with context, a new formalism is required toward a contextual theory of concepts. SCOP is considered a promising formalism in this sense and is briefly described.


On the bit-complexity of sparse polynomial multiplication

Abstract: In this paper, we present fast algorithms for the product of two multivariate polynomials in sparse representation. The bit complexity of our algorithms are studied in detail for various types of coefficients, and we derive new complexity results for the power series multiplication in many variables. Our algorithms are implemented and freely available within the Mathemagix software. We show that their theoretical costs are well-reflected in practice.


Performance of Buchberger's Improved Algorithm using Prime Based Ordering

Abstract: Prime-based ordering which is proved to be admissible, is the encoding of indeterminates in power-products with prime numbers and ordering them by using the natural number order. Using Eiffel, four versions of Buchberger's improved algorithm for obtaining Groebner Bases have been developed: two total degree versions, representing power products as strings and the other two as integers based on prime-based ordering. The versions are further distinguished by implementing coefficients as 64-bit integers and as multiple-precision integers. By using primebased power product coding, iterative or recursive operations on power products are replaced with integer operations. It is found that on a series of example polynomial sets, significant reductions in computation time of 30% or more are almost always obtained.


ALLSAT compressed with wildcards: All, or all maximum independent sets

Abstract: An odd cycle cover is a vertex set whose removal makes a graph bipartite. We show that if a $k$-element odd cycle cover of a graph with w vertices is known then all $N$ maximum anticliques (= independent sets) can be generated in time $O(2^k w^3 + N w^2))$. Generating ${\it all}\ N'$ anticliques (maximum or not) is easier and works for arbitrary graphs in time $O(N'w^2)$. In fact the use of wildcards allows to compactly generate the anticliques in clusters.


Neighbourhood Structures: Bisimilarity and Basic Model Theory

Abstract: Neighbourhood structures are the standard semantic tool used to reason about non-normal modal logics. The logic of all neighbourhood models is called classical modal logic. In coalgebraic terms, a neighbourhood frame is a coalgebra for the contravariant powerset functor composed with itself, denoted by 2^2. We use this coalgebraic modelling to derive notions of equivalence between neighbourhood structures. 2^2-bisimilarity and behavioural equivalence are well known coalgebraic concepts, and they are distinct, since 2^2 does not preserve weak pullbacks. We introduce a third, intermediate notion whose witnessing relations we call precocongruences (based on pushouts). We give back-and-forth style characterisations for 2^2-bisimulations and precocongruences, we show that on a single coalgebra, precocongruences capture behavioural equivalence, and that between neighbourhood structures, precocongruences are a better approximation of behavioural equivalence than 2^2-bisimulations. We also introduce a notion of modal saturation for neighbourhood models, and investigate its relationship with definability and image-finiteness. We prove a Hennessy-Milner theorem for modally saturated and for image-finite neighbourhood models. Our main results are an analogue of Van Benthem's characterisation theorem and a model-theoretic proof of Craig interpolation for classical modal logic.


Ethemba Trusted Host EnvironmentMainly Based on Attestation

Abstract: Ethemba provides a framework and demonstrator for TPM applications.


Everyone is a Curator: Human-Assisted Preservation for ORE Aggregations

Abstract: The Open Archives Initiative (OAI) has recently created the Object Reuse and Exchange (ORE) project that defines Resource Maps (ReMs) for describing aggregations of web resources. These aggregations are susceptible to many of the same preservation challenges that face other web resources. In this paper, we investigate how the aggregations of web resources can be preserved outside of the typical repository environment and instead rely on the thousands of interactive users in the web community and the Web Infrastructure (the collection of web archives, search engines, and personal archiving services) to facilitate preservation. Inspired by Web 2.0 services such as digg, deli.cio.us, and Yahoo! Buzz, we have developed a lightweight system called ReMember that attempts to harness the collective abilities of the web community for preservation purposes instead of solely placing the burden of curatorial responsibilities on a small number of experts.


Fast Dual-Radio Cross-Layer Handoffs in Multi-Hop Infrastructure-mode 802.11 Wireless Networks for In-Vehicle Multimedia Infotainment

Abstract: Minimizing handoff latency and achieving near-zero packet loss is critical for delivering multimedia infotainment applications to fast-moving vehicles that are likely to encounter frequent handoffs. In this paper, we propose a dual-radio cross-layer handoff scheme for infrastructure-mode 802.11 Wireless Networks that achieve this goal. We present performance results of an implementation of our algorithm in a Linux-based On-Board-Unit prototype.


A Quantum Key Distribution Network Through Single Mode Optical Fiber

Abstract: Quantum key distribution (QKD) has been developed within the last decade that is provably secure against arbitrary computing power, and even against quantum computer attacks. Now there is a strong need of research to exploit this technology in the existing communication networks. In this paper we have presented various experimental results pertaining to QKD like Raw key rate and Quantum bit error rate (QBER). We found these results over 25 km single mode optical fiber. The experimental setup implemented the enhanced version of BB84 QKD protocol. Based upon the results obtained, we have presented a network design which can be implemented for the realization of large scale QKD networks. Furthermore, several new ideas are presented and discussed to integrate the QKD technique in the classical communication networks.


Square root meadows

Abstract: Let Q_0 denote the rational numbers expanded to a meadow by totalizing inversion such that 0^{-1}=0. Q_0 can be expanded by a total sign function s that extracts the sign of a rational number. In this paper we discuss an extension Q_0(s ,\sqrt) of the signed rationals in which every number has a unique square root.


Arrow's Impossibility Theorem Without Unanimity

Abstract: Arrow's Impossibility Theorem states that any constitution which satisfies Transitivity, Independence of Irrelevant Alternatives (IIA) and Unanimity is a dictatorship. Wilson derived properties of constitutions satisfying Transitivity and IIA for unrestricted domains where ties are allowed. In this paper we consider the case where only strict preferences are allowed. In this case we derive a new short proof of Arrow theorem and further obtain a new and complete characterization of all functions satisfying Transitivity and IIA.


Alpaga: A Tool for Solving Parity Games with Imperfect Information

Abstract: Alpaga is a solver for two-player parity games with imperfect information. Given the description of a game, it determines whether the first player can ensure to win and, if so, it constructs a winning strategy. The tool provides a symbolic implementation of a recent algorithm based on antichains.


On finding multiplicities of characteristic polynomial factors of black-box matrices

Abstract: We present algorithms and heuristics to compute the characteristic polynomial of a matrix given its minimal polynomial. The matrix is represented as a black-box, i.e., by a function to compute its matrix-vector product. The methods apply to matrices either over the integers or over a large enough finite field. Experiments show that these methods perform efficiently in practice. Combined in an adaptive strategy, these algorithms reach significant speedups in practice for some integer matrices arising in an application from graph theory.


A Knowledge Discovery Framework for Learning Task Models from User Interactions in Intelligent Tutoring Systems

Abstract: Domain experts should provide relevant domain knowledge to an Intelligent Tutoring System (ITS) so that it can guide a learner during problemsolving learning activities. However, for many ill-defined domains, the domain knowledge is hard to define explicitly. In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions, and how it can support tutoring services during problem-solving exercises. This article describes an extension of this approach to extract a problem space that is richer and more adapted for supporting tutoring services. We combined sequential pattern mining with (1) dimensional pattern mining (2) time intervals, (3) the automatic clustering of valued actions and (4) closed sequences mining. Some tutoring services have been implemented and an experiment has been conducted in a tutoring system.


Optimizing Service Orchestrations

Abstract: As the number of services and the size of data involved in workflows increases, centralised orchestration techniques are reaching the limits of scalability. In the classic orchestration model, all data passes through a centralised engine, which results in unnecessary data transfer, wasted bandwidth and the engine to become a bottleneck to the execution of a workflow. This paper presents and evaluates the Circulate architecture which maintains the robustness and simplicity of centralised orchestration, but facilitates choreography by allowing services to exchange data directly with one another. Circulate could be realised within any existing workflow framework, in this paper, we focus on WS-Circulate, a Web services based implementation. Taking inspiration from the Montage workflow, a number of common workflow patterns (sequence, fan-in and fan-out), input to output data size relationships and network configurations are identified and evaluated. The performance analysis concludes that a substantial reduction in communication overhead results in a 2-4 fold performance benefit across all patterns. An end-to-end pattern through the Montage workflow results in an 8 fold performance benefit and demonstrates how the advantage of using the Circulate architecture increases as the complexity of a workflow grows.


Space Efficient Secret Sharing

Abstract: This note proposes a method of space efficient secret sharing in which k secrets are mapped into n shares (n>=k) of the same size. Since, n can be chosen to be equal to k, the method is space efficient. This method may be compared with conventional secret sharing schemes that divide a single secret into n shares.


Space Efficient Secret Sharing: A Recursive Approach

Abstract: This paper presents a recursive secret sharing technique that distributes k-1 secrets of length b each into n shares such that each share is effectively of length (n/(k-1))*b and any k pieces suffice for reconstructing all the k-1 secrets. Since n/(k-1) is near the optimal factor of n/k, and can be chosen to be close to 1, the proposed technique is space efficient. Furthermore, each share is information theoretically secure, i.e. it does not depend on any unproven assumption of computational intractability. Such a recursive technique has potential applications in secure and reliable storage of information on the Web and in sensor networks.


A Mathematical Basis for the Chaining of Lossy Interface Adapters

Abstract: Despite providing similar functionality, multiple network services may require the use of different interfaces to access the functionality, and this problem will only get worse with the widespread deployment of ubiquitous computing environments. One way around this problem is to use interface adapters that adapt one interface into another. Chaining these adapters allows flexible interface adaptation with fewer adapters, but the loss incurred due to imperfect interface adaptation must be considered. This paper outlines a mathematical basis for analyzing the chaining of lossy interface adapters. We also show that the problem of finding an optimal interface adapter chain is NP-complete.


Adaptive algorithms for identifying large flows in IP traffic

Abstract: We propose in this paper an on-line algorithm based on Bloom filters for identifying large flows in IP traffic (a.k.a. elephants). Because of the large number of small flows, hash tables of these algorithms have to be regularly refreshed. Recognizing that the periodic erasure scheme usually used in the technical literature turns out to be quite inefficient when using real traffic traces over a long period of time, we introduce a simple adaptive scheme that closely follows the variations of traffic. When tested against real traffic traces, the proposed on-line algorithm performs well in the sense that the detection ratio of long flows by the algorithm over a long time period is quite high. Beyond the identification of elephants, this same class of algorithms is applied to the closely related problem of detection of anomalies in IP traffic, e.g., SYN flood due for instance to attacks. An algorithm for detecting SYN and volume flood anomalies in Internet traffic is designed. Experiments show that an anomaly is detected in less than one minute and the targeted destinations are identified at the same time.


Non-Confluent NLC Graph Grammar Inference by Compressing Disjoint Subgraphs

Abstract: Grammar inference deals with determining (preferable simple) models/grammars consistent with a set of observations. There is a large body of research on grammar inference within the theory of formal languages. However, there is surprisingly little known on grammar inference for graph grammars. In this paper we take a further step in this direction and work within the framework of node label controlled (NLC) graph grammars. Specifically, we characterize, given a set of disjoint and isomorphic subgraphs of a graph $G$, whether or not there is a NLC graph grammar rule which can generate these subgraphs to obtain $G$. This generalizes previous results by assuming that the set of isomorphic subgraphs is disjoint instead of non-touching. This leads naturally to consider the more involved ``non-confluent'' graph grammar rules.


A historical perspective on developing foundations iInfo(TM) information systems: iConsult(TM) and iEntertain(TM) apps using iDescribers(TM) information integration for iOrgs(TM) information systems

Abstract: Technology now at hand can integrate all kinds of digital information for individuals, groups, and organizations so their information usefully links together. iInfo(TM) information integration works by making connections including examples like the following: - A statistical connection between "being in a traffic jam" and "driving in downtown Trenton between 5PM and 6PM on a weekday." - A terminological connection between "MSR" and "Microsoft Research." - A causal connection between "joining a group" and "being a member of the group." - A syntactic connection between "a pin dropped" and "a dropped pin." - A biological connection between "a dolphin" and "a mammal". - A demographic connection between "undocumented residents of California" and "7% of the population of California." - A geographical connection between "Leeds" and "England." - A temporal connection between "turning on a computer" and "joining an on-line discussion." By making these connections, iInfo offers tremendous value for individuals, families, groups, and organizations in making more effective use of information technology. In practice, integrated information is invariably pervasively inconsistent. Therefore iInfo must be able to make connections even in the face of inconsistency. The business of iInfo is not to make difficult decisions like deciding the ultimate truth or probability of propositions. Instead it provides means for processing information and carefully recording its provenance including arguments (including arguments about arguments) for and against propositions that is used by iConsult(TM) and iEntertain(TM) apps in iOrgs(TM) Information Systems. A historical perspective on the above questions is highly pertinent to the current quest to develop foundations for privacy-friendly client-cloud computing.


A Keygraph Classification Framework for Real-Time Object Detection

Abstract: In this paper, we propose a new approach for keypoint-based object detection. Traditional keypoint-based methods consist in classifying individual points and using pose estimation to discard misclassifications. Since a single point carries no relational features, such methods inherently restrict the usage of structural information to the pose estimation phase. Therefore, the classifier considers purely appearance-based feature vectors, thus requiring computationally expensive feature extraction or complex probabilistic modelling to achieve satisfactory robustness. In contrast, our approach consists in classifying graphs of keypoints, which incorporates structural information during the classification phase and allows the extraction of simpler feature vectors that are naturally robust. In the present work, 3-vertices graphs have been considered, though the methodology is general and larger order graphs may be adopted. Successful experimental results obtained for real-time object detection in video sequences are reported.


How Emotional Mechanism Helps Episodic Learning in a Cognitive Agent

Abstract: In this paper we propose the CTS (Concious Tutoring System) technology, a biologically plausible cognitive agent based on human brain functions.This agent is capable of learning and remembering events and any related information such as corresponding procedures, stimuli and their emotional valences. Our proposed episodic memory and episodic learning mechanism are closer to the current multiple-trace theory in neuroscience, because they are inspired by it [5] contrary to other mechanisms that are incorporated in cognitive agents. This is because in our model emotions play a role in the encoding and remembering of events. This allows the agent to improve its behavior by remembering previously selected behaviors which are influenced by its emotional mechanism. Moreover, the architecture incorporates a realistic memory consolidation process based on a data mining algorithm.


CPAchecker: A Tool for Configurable Software Verification

Abstract: Configurable software verification is a recent concept for expressing different program analysis and model checking approaches in one single formalism. This paper presents CPAchecker, a tool and framework that aims at easy integration of new verification components. Every abstract domain, together with the corresponding operations, is required to implement the interface of configurable program analysis (CPA). The main algorithm is configurable to perform a reachability analysis on arbitrary combinations of existing CPAs. The major design goal during the development was to provide a framework for developers that is flexible and easy to extend. We hope that researchers find it convenient and productive to implement new verification ideas and algorithms using this platform and that it advances the field by making it easier to perform practical experiments. The tool is implemented in Java and runs as command-line tool or as Eclipse plug-in. We evaluate the efficiency of our tool on benchmarks from the software model checker BLAST. The first released version of CPAchecker implements CPAs for predicate abstraction, octagon, and explicit-value domains. Binaries and the source code of CPAchecker are publicly available as free software.


Cut-Simulation and Impredicativity

Abstract: We investigate cut-elimination and cut-simulation in impredicative (higher-order) logics. We illustrate that adding simple axioms such as Leibniz equations to a calculus for an impredicative logic -- in our case a sequent calculus for classical type theory -- is like adding cut. The phenomenon equally applies to prominent axioms like Boolean- and functional extensionality, induction, choice, and description. This calls for the development of calculi where these principles are built-in instead of being treated axiomatically.


Bounds on the Size of Small Depth Circuits for Approximating Majority

Abstract: In this paper, we show that for every constant $0 < \epsilon < 1/2$ and for every constant $d \geq 2$, the minimum size of a depth $d$ Boolean circuit that $\epsilon$-approximates Majority function on $n$ variables is exp$(\Theta(n^{1/(2d-2)}))$. The lower bound for every $d \geq 2$ and the upper bound for $d=2$ have been previously shown by O'Donnell and Wimmer [ICALP'07], and the contribution of this paper is to give a matching upper bound for $d \geq 3$.


An Alternative Cracking of The Genetic Code

Abstract: We Propose 22 unique Solutions to the Genetic Code. An Alternative Cracking, from the Perspective of a Mathematician.


On a problem of Frobenius in three numbers

Abstract: For three positive integers ai, aj, ak pairwise coprime, we present an algorithm that find the least multiple of ai that is a positive linear combination of aj, ak. The average running time of this algorithm is O(1). Using this algorithm and the chinese remainder theorem leads to a direct computation of the Frobenius number f(a1, a2, a3).


The Complexity of Nash Equilibria in Simple Stochastic Multiplayer Games

Abstract: We analyse the computational complexity of finding Nash equilibria in simple stochastic multiplayer games. We show that restricting the search space to equilibria whose payoffs fall into a certain interval may lead to undecidability. In particular, we prove that the following problem is undecidable: Given a game G, does there exist a pure-strategy Nash equilibrium of G where player 0 wins with probability 1. Moreover, this problem remains undecidable if it is restricted to strategies with (unbounded) finite memory. However, if mixed strategies are allowed, decidability remains an open problem. One way to obtain a provably decidable variant of the problem is restricting the strategies to be positional or stationary. For the complexity of these two problems, we obtain a common lower bound of NP and upper bounds of NP and PSPACE respectively.


Graph Sparsification in the Semi-streaming Model

Abstract: Analyzing massive data sets has been one of the key motivations for studying streaming algorithms. In recent years, there has been significant progress in analysing distributions in a streaming setting, but the progress on graph problems has been limited. A main reason for this has been the existence of linear space lower bounds for even simple problems such as determining the connectedness of a graph. However, in many new scenarios that arise from social and other interaction networks, the number of vertices is significantly less than the number of edges. This has led to the formulation of the semi-streaming model where we assume that the space is (near) linear in the number of vertices (but not necessarily the edges), and the edges appear in an arbitrary (and possibly adversarial) order. In this paper we focus on graph sparsification, which is one of the major building blocks in a variety of graph algorithms. There has been a long history of (non-streaming) sampling algorithms that provide sparse graph approximations and it a natural question to ask if the sparsification can be achieved using a small space, and in addition using a single pass over the data? The question is interesting from the standpoint of both theory and practice and we answer the question in the affirmative, by providing a one pass $\tilde{O}(n/\epsilon^{2})$ space algorithm that produces a sparsification that approximates each cut to a $(1+\epsilon)$ factor. We also show that $\Omega(n \log \frac1\epsilon)$ space is necessary for a one pass streaming algorithm to approximate the min-cut, improving upon the $\Omega(n)$ lower bound that arises from lower bounds for testing connectivity.


Over-enhancement Reduction in Local Histogram Equalization using its Degrees of Freedom

Abstract: A well-known issue of local (adaptive) histogram equalization (LHE) is over-enhancement (i.e., generation of spurious details) in homogenous areas of the image. In this paper, we show that the LHE problem has many solutions due to the ambiguity in ranking pixels with the same intensity. The LHE solution space can be searched for the images having the maximum PSNR or structural similarity (SSIM) with the input image. As compared to the results of the prior art, these solutions are more similar to the input image while offering the same local contrast. Index Terms: histogram modification or specification, contrast enhancement


Hierarchical Triple-Modular Redundancy (H-TMR) Network For Digital Systems

Abstract: Hierarchical application of Triple-Modular Redundancy (TMR) increases fault tolerance of digital Integrated Circuit (IC). In this paper, a simple probabilistic model was proposed for analysis of fault masking performance of hierarchical TMR networks. Performance improvements obtained by second order TMR network were theoretically compared with first order TMR network.


Immunity and Pseudorandomness of Context-Free Languages

Abstract: We discuss the computational complexity of context-free languages, concentrating on two well-known structural properties---immunity and pseudorandomness. An infinite language is REG-immune (resp., CFL-immune) if it contains no infinite subset that is a regular (resp., context-free) language. We prove that (i) there is a context-free REG-immune language outside REG/n and (ii) there is a REG-bi-immune language that can be computed deterministically using logarithmic space. We also show that (iii) there is a CFL-simple set, where a CFL-simple language is an infinite context-free language whose complement is CFL-immune. Similar to the REG-immunity, a REG-primeimmune language has no polynomially dense subsets that are also regular. We further prove that (iv) there is a context-free language that is REG/n-bi-primeimmune. Concerning pseudorandomness of context-free languages, we show that (v) CFL contains REG/n-pseudorandom languages. Finally, we prove that (vi) against REG/n, there exists an almost 1-1 pseudorandom generator computable in nondeterministic pushdown automata equipped with a write-only output tape and (vii) against REG, there is no almost 1-1 weakly pseudorandom generator computable deterministically in linear time by a single-tape Turing machine.


Malware Detection using Attribute-Automata to parse Abstract Behavioral Descriptions

Abstract: Most behavioral detectors of malware remain specific to a given language and platform, mostly PE executables for Windows. The objective of this paper is to define a generic approach for behavioral detection based on two layers respectively responsible for abstraction and detection. The first abstraction layer remains specific to a platform and a language. This first layer interprets the collected instructions, API calls and arguments and classifies these operations as well as the involved objects according to their purpose in the malware lifecycle. The second detection layer remains generic and is totally interoperable between the different abstraction components. This layer relies on parallel automata parsing attribute-grammars where semantic rules are used for object typing (object classification) and object binding (data-flow). To feed detection and to experiment with our approach we have developed two different abstraction components: one processing system call traces from native code and one processing the VBScript interpreted language. The different experimentations have provided promising detection rates, in particular for script files (89%), with almost none false positives. In the case of process traces, the detection rate remains significant (51%) but could be increased by more sophisticated collection tools.


Non-monotone submodular maximization under matroid and knapsack constraints

Abstract: Submodular function maximization is a central problem in combinatorial optimization, generalizing many important problems including Max Cut in directed/undirected graphs and in hypergraphs, certain constraint satisfaction problems, maximum entropy sampling, and maximum facility location problems. Unlike submodular minimization, submodular maximization is NP-hard. For the problem of maximizing a non-monotone submodular function, Feige, Mirrokni, and Vondr\'ak recently developed a $2\over 5$-approximation algorithm \cite{FMV07}, however, their algorithms do not handle side constraints.} In this paper, we give the first constant-factor approximation algorithm for maximizing any non-negative submodular function subject to multiple matroid or knapsack constraints. We emphasize that our results are for {\em non-monotone} submodular functions. In particular, for any constant $k$, we present a $({1\over k+2+{1\over k}+\epsilon})$-approximation for the submodular maximization problem under $k$ matroid constraints, and a $({1\over 5}-\epsilon)$-approximation algorithm for this problem subject to $k$ knapsack constraints ($\epsilon>0$ is any constant). We improve the approximation guarantee of our algorithm to ${1\over k+1+{1\over k-1}+\epsilon}$ for $k\ge 2$ partition matroid constraints. This idea also gives a $({1\over k+\epsilon})$-approximation for maximizing a {\em monotone} submodular function subject to $k\ge 2$ partition matroids, which improves over the previously best known guarantee of $\frac{1}{k+1}$.


On the complexity of Nash dynamics and Sink Equilibria

Abstract: Studying Nash dynamics is an important approach for analyzing the outcome of games with repeated selfish behavior of self-interested agents. Sink equilibria has been introduced by Goemans, Mirrokni, and Vetta for studying social cost on Nash dynamics over pure strategies in games. However, they do not address the complexity of sink equilibria in these games. Recently, Fabrikant and Papadimitriou initiated the study of the complexity of Nash dynamics in two classes of games. In order to completely understand the complexity of Nash dynamics in a variety of games, we study the following three questions for various games: (i) given a state in game, can we verify if this state is in a sink equilibrium or not? (ii) given an instance of a game, can we verify if there exists any sink equilibrium other than pure Nash equilibria? and (iii) given an instance of a game, can we verify if there exists a pure Nash equilibrium (i.e, a sink equilibrium with one state)? In this paper, we almost answer all of the above questions for a variety of classes of games with succinct representation, including anonymous games, player-specific and weighted congestion games, valid-utility games, and two-sided market games. In particular, for most of these problems, we show that (i) it is PSPACE-complete to verify if a given state is in a sink equilibrium, (ii) it is NP-hard to verify if there exists a pure Nash equilibrium in the game or not, (iii) it is PSPACE-complete to verify if there exists any sink equilibrium other than pure Nash equilibria. To solve these problems, we illustrate general techniques that could be used to answer similar questions in other classes of games.


On the Applicability of Combinatorial Designs to Key Predistribution for Wireless Sensor Networks

Abstract: The constraints of lightweight distributed computing environments such as wireless sensor networks lend themselves to the use of symmetric cryptography to provide security services. The lack of central infrastructure after deployment of such networks requires the necessary symmetric keys to be predistributed to participating nodes. The rich mathematical structure of combinatorial designs has resulted in the proposal of several key predistribution schemes for wireless sensor networks based on designs. We review and examine the appropriateness of combinatorial designs as a tool for building key predistribution schemes suitable for such environments.