Results 1  10
of
43
A KeyManagement Scheme for Distributed Sensor Networks
 In Proceedings of the 9th ACM Conference on Computer and Communications Security
, 2002
"... Distributed Sensor Networks (DSNs) are adhoc mobile networks that include sensor nodes with limited computation and communication capabilities. DSNs are dynamic in the sense that they allow addition and deletion of sensor nodes after deployment to grow the network or replace failing and unreliable ..."
Abstract

Cited by 585 (4 self)
 Add to MetaCart
Distributed Sensor Networks (DSNs) are adhoc mobile networks that include sensor nodes with limited computation and communication capabilities. DSNs are dynamic in the sense that they allow addition and deletion of sensor nodes after deployment to grow the network or replace failing and unreliable nodes. DSNs may be deployed in hostile areas where communication is monitored and nodes are subject to capture and surreptitious use by an adversary. Hence DSNs require cryptographic protection of communications, sensorcapture detection, key revocation and sensor disabling. In this paper, we present a keymanagement scheme designed to satisfy both operational and security requirements of DSNs.
Random key predistribution schemes for sensor networks
 IN PROCEEDINGS OF THE 2003 IEEE SYMPOSIUM ON SECURITY AND PRIVACY
, 2003
"... Key establishment in sensor networks is a challenging problem because asymmetric key cryptosystems are unsuitable for use in resource constrained sensor nodes, and also because the nodes could be physically compromised by an adversary. We present three new mechanisms for key establishment using the ..."
Abstract

Cited by 543 (15 self)
 Add to MetaCart
Key establishment in sensor networks is a challenging problem because asymmetric key cryptosystems are unsuitable for use in resource constrained sensor nodes, and also because the nodes could be physically compromised by an adversary. We present three new mechanisms for key establishment using the framework of predistributing a random set of keys to each node. First, in the qcomposite keys scheme, we trade off the unlikeliness of a largescale network attack in order to significantly strengthen random key predistribution’s strength against smallerscale attacks. Second, in the multipathreinforcement scheme, we show how to strengthen the security between any two nodes by leveraging the security of other links. Finally, we present the randompairwise keys scheme, which perfectly preserves the secrecy of the rest of the network when any node is captured, and also enables nodetonode authentication and quorumbased revocation.
ProClust: Improved Clustering of Protein Sequences with an extended graphbased approach
, 2002
"... Motivation: The problem of finding remote homologues of a given protein sequence via alignment methods is not fully solved. In fact, the task seems to become more difficult with more data. As the size of the database increases, so does the noise level; the highest alignment scores due to random sim ..."
Abstract

Cited by 15 (0 self)
 Add to MetaCart
Motivation: The problem of finding remote homologues of a given protein sequence via alignment methods is not fully solved. In fact, the task seems to become more difficult with more data. As the size of the database increases, so does the noise level; the highest alignment scores due to random similarities increase and can be higher than the alignment score between true homologues. Comparing two sequences with an arbitrary alignment method yields a similarity value which may indicate an evolutionary relationship between them. A threshold value is usually chosen to distinguish between true homologue relationships and random similarities. To compensate for the higher probability of spurious hits in larger databases, this threshold is increased. Increasing specificity however leads to decreased sensitivity as a matter of principle.
Upper Tails for Subgraph Counts in Random Graphs
 ISRAEL J. MATH
, 2002
"... Let G be a fixed graph and let XG be the number of copies of G contained in the random graph G(n, p). We prove exponential bounds on the upper tail of XG which are best possible up to a logarithmic factor in the exponent. Our argument relies on an extension of Alon's result about the maximum num ..."
Abstract

Cited by 15 (4 self)
 Add to MetaCart
Let G be a fixed graph and let XG be the number of copies of G contained in the random graph G(n, p). We prove exponential bounds on the upper tail of XG which are best possible up to a logarithmic factor in the exponent. Our argument relies on an extension of Alon's result about the maximum number of copies of G in a graph with a given number of edges. Similar bounds are proved for the random graph G(n, M) too.
Highly reliable trust establishment scheme in ad hoc networks
 Computer Networks
, 2004
"... Securing ad hoc networks in a fully selforganized way is effective and lightweight, but fails to accomplish trust initialization in many trust deficient scenarios. To overcome this problem, this paper aims at building well established trust relationships in ad hoc networks without relying on any p ..."
Abstract

Cited by 13 (0 self)
 Add to MetaCart
Securing ad hoc networks in a fully selforganized way is effective and lightweight, but fails to accomplish trust initialization in many trust deficient scenarios. To overcome this problem, this paper aims at building well established trust relationships in ad hoc networks without relying on any predefined assumption. We propose a probabilistic solution based on distributed trust model. A secret dealer is introduced only in the system bootstrapping phase to complement the assumption in trust initialization. With it, much shorter and more robust trust chains are able to be constructed with high probability. A fully selforganized trust establishment approach is then adopted to conform to the dynamic membership changes. The simulation results on both static and dynamic performances show that our scheme is highly resilient to dynamic membership changing and scales well. The lack of initial trust establishment mechanisms in most higher level security solutions (e.g. key management schemes, secure routing protocols) for ad hoc networks makes them benefit from our scheme. Key words: ad hoc networks, security, trust management, distributed trust model 1
How complex are random graphs in first order logic
"... It is not hard to write a first order formula which is true for a given graph G but is false for any graph not isomorphic to G. The smallest number D(G) of nested quantifiers in a such formula can serve as a measure for the “first order complexity ” of G. Here, this parameter is studied for random g ..."
Abstract

Cited by 12 (9 self)
 Add to MetaCart
It is not hard to write a first order formula which is true for a given graph G but is false for any graph not isomorphic to G. The smallest number D(G) of nested quantifiers in a such formula can serve as a measure for the “first order complexity ” of G. Here, this parameter is studied for random graphs. We determine it asymptotically when the edge probability p is constant; in fact, D(G) is of order log n then. For very sparse graphs its magnitude is Θ(n). On the other hand, for certain (carefully chosen) values of p the parameter D(G) can drop down to the very slow growing function log ∗ n, the inverse of the TOWERfunction. The general picture, however, is still a mystery. 1
The First Order Definability of Graphs: Upper Bounds for Quantifier Depth
"... ... In passing we establish an upper bound for a related number D(G, G0), the minimum quantifier depth of a first order sentence which is true on exactly one of graphs G and G0. If G and G0 are nonisomorphic and both have n vertices, then D(G, G0) < = (n + 3)/2. This bound is tight up to an additiv ..."
Abstract

Cited by 10 (4 self)
 Add to MetaCart
... In passing we establish an upper bound for a related number D(G, G0), the minimum quantifier depth of a first order sentence which is true on exactly one of graphs G and G0. If G and G0 are nonisomorphic and both have n vertices, then D(G, G0) < = (n + 3)/2. This bound is tight up to an additive constant of 1. If we additionally require that a sentence distinguishing G and G0 is existential, we prove only a slightly weaker bound D(G, G0) < = (n + 5)/2.
Key Distribution Techniques For Sensor Networks
"... This chapter reviews several key distribution and key establishment techniques for sensor networks. We briefly describe several well known key establishment schemes, and provide a more detailed discussion of our work on random key distribution in particular. ..."
Abstract

Cited by 10 (2 self)
 Add to MetaCart
This chapter reviews several key distribution and key establishment techniques for sensor networks. We briefly describe several well known key establishment schemes, and provide a more detailed discussion of our work on random key distribution in particular.
Monochromatic and heterochromatic subgraphs in edgecolored graphsa survey
 Graphs and Combinatorics
, 2008
"... Abstract. Let Kn be the complete graph with n vertices and c1,c2, · · ·,cr be r different colors. Suppose we randomly and uniformly color the edges of Kn in c1,c2, · · ·,cr. Then we get a random graph, denoted by Kr n. In the paper, we investigate the asymptotic properties of several kinds of ..."
Abstract

Cited by 9 (1 self)
 Add to MetaCart
Abstract. Let Kn be the complete graph with n vertices and c1,c2, · · ·,cr be r different colors. Suppose we randomly and uniformly color the edges of Kn in c1,c2, · · ·,cr. Then we get a random graph, denoted by Kr n. In the paper, we investigate the asymptotic properties of several kinds of monochromatic and heterochromatic subgraphs in Kr n. Accurate threshold functions in some cases are also obtained.
Modeling Pairwise Key Establishment for Random Key Predistribution in LargeScale Sensor Networks
, 2004
"... Abstract — Sensor networks are composed of a large number of low power sensor devices. For secure communication among sensors, secret keys are required to be established between them. Considering the storage limitations and the lack of postdeployment configuration information of sensors, Random Key ..."
Abstract

Cited by 7 (2 self)
 Add to MetaCart
Abstract — Sensor networks are composed of a large number of low power sensor devices. For secure communication among sensors, secret keys are required to be established between them. Considering the storage limitations and the lack of postdeployment configuration information of sensors, Random Key Predistribution schemes have been proposed. Due to limited number of keys, sensors can only share keys with a subset of the neighboring sensors. Sensors then use these neighbors to establish pairwise keys with the remaining neighbors. In order to study the communication overhead incurred due to pairwise key establishment, we derive probability models to design and analyze pairwise key establishment schemes for largescale sensor networks. Our model applies the binomial distribution and a modified binomial distribution and analyzes the key path length in a hopbyhop fashion. We also validate our models through a systematic validation procedure. We then show the robustness of our results and illustrate how our models can be used for addressing sensor network design problems. I.