LEADER 05905nam 22006135 450 001 996466352603316 005 20200701003249.0 010 $a1-280-30793-5 010 $a9786610307937 010 $a3-540-25840-X 024 7 $a10.1007/b104265 035 $a(CKB)1000000000212660 035 $a(SSID)ssj0000100318 035 $a(PQKBManifestationID)11113560 035 $a(PQKBTitleCode)TC0000100318 035 $a(PQKBWorkID)10036659 035 $a(PQKB)11447393 035 $a(DE-He213)978-3-540-25840-7 035 $a(MiAaPQ)EBC3068309 035 $a(PPN)134123557 035 $a(EXLCZ)991000000000212660 100 $a20100904d2005 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 10$aAgents and Peer-to-Peer Computing$b[electronic resource] $eSecond International Workshop, AP2PC 2003, Melbourne, Australia, July 14, 2003, Revised and Invited Papers /$fedited by Gianluca Moro, Claudio Sartori, Munindar P. Singh 205 $a1st ed. 2005. 210 1$aBerlin, Heidelberg :$cSpringer Berlin Heidelberg :$cImprint: Springer,$d2005. 215 $a1 online resource (XII, 205 p.) 225 1 $aLecture Notes in Artificial Intelligence ;$v2872 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-24053-5 320 $aIncludes bibliographical references and index. 327 $aParadigm Integration and Challenges -- Information Acquisition Through an Integrated Paradigm: Agent + Peer-to-Peer -- Robustness Challenges in Peer-to-Peer Agent Systems -- Trust -- Bayesian Network Trust Model in Peer-to-Peer Networks -- Agent-Based Social Assessment of Shared Resources -- A Passport-Like Service over an Agent-Based Peer-to-Peer Network -- Self-Organization -- A Robust and Scalable Peer-to-Peer Gossiping Protocol -- Group Formation Among Peer-to-Peer Agents: Learning Group Characteristics -- A Pheromone-Based Coordination Mechanism Applied in Peer-to-Peer -- Incentives -- Incentive Mechanisms for Peer-to-Peer Systems -- A Taxonomy of Incentive Patterns -- Search and Systems -- P2P MetaData Search Layers -- A Peer-to-Peer Information System for the Semantic Web -- G-Grid: A Class of Scalable and Self-Organizing Data Structures for Multi-dimensional Querying and Content Routing in P2P Networks -- Fuzzy Cost Modeling for Peer-to-Peer Systems -- A P2P Approach to ClassLoading in Java -- Adaptive Applications -- Multi-agent Interaction Technology for Peer-to-Peer Computing in Electronic Trading Environments -- Location-Based and Content-Based Information Access in Mobile Peer-to-Peer Computing: The TOTA Approach -- K-Trek: A Peer-to-Peer Approach to Distribute Knowledge in Large Environments -- Mobile Agents -- Improving Peer-to-Peer Resource Discovery Using Mobile Agent Based Referrals -- Mobile Agents for Locating Documents in Ad Hoc Networks. 330 $aPeer-to-peer (P2P) computing is currently attracting enormous public attention, spurred by the popularity of file-sharing systems such as Napster, Gnutella, Morpheus, Kaza, and several others. In P2P systems, a very large number of autonomous computing nodes, the peers, rely on each other for services. P2P networks are emerging as a new distributed computing paradigm because of their potential to harness the computing power and the storage capacity of the hosts composing the network, and because they realize a completely open decentralized environment where everybody can join in autonomously. Although researchers working on distributed computing, multiagent systems, databases, and networks have been using similar concepts for a long time, it is only recently that papers motivated by the current P2P paradigm have started appearing in high quality conferences and workshops. In particular, research on agent systems appears to be most relevant because multiagent systems have always been thought of as networks of autonomous peers since their inception. Agents, which can be superimposed on the P2P architecture, embody the description of task environments, decision-support capabilities, social behaviors, trust and reputation, and interaction protocols among peers. The emphasis on decentralization, autonomy, ease, and speed of growth that gives P2P its advantages also leads to significant potential problems. Most prominent among these are coordination ? the ability of an agent to make decisions on its own actions in the context of activities of other agents, and scalability ? the value of the P2P systems in how well they self-organize so as to scale along several dimensions, including complexity, heterogeneity of peers, robustness, traffic redistribution, etc. This book brings together an introduction, three invited articles, and revised versions of the papers presented at the Second International Workshop on Agents and Peer-to-Peer Computing, AP2PC 2003, held in Melbourne, Australia, July 2003. 410 0$aLecture Notes in Artificial Intelligence ;$v2872 606 $aComputer communication systems 606 $aArtificial intelligence 606 $aComputer Communication Networks$3https://scigraph.springernature.com/ontologies/product-market-codes/I13022 606 $aArtificial Intelligence$3https://scigraph.springernature.com/ontologies/product-market-codes/I21000 615 0$aComputer communication systems. 615 0$aArtificial intelligence. 615 14$aComputer Communication Networks. 615 24$aArtificial Intelligence. 676 $a004.6/5 702 $aMoro$b Gianluca$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSartori$b Claudio$4edt$4http://id.loc.gov/vocabulary/relators/edt 702 $aSingh$b Munindar P$4edt$4http://id.loc.gov/vocabulary/relators/edt 906 $aBOOK 912 $a996466352603316 996 $aAgents and Peer-to-Peer Computing$9772342 997 $aUNISA LEADER 11839nam 2200697Ia 450 001 9910955382503321 005 20251116221136.0 010 $a1-61209-732-4 035 $a(CKB)2560000000069961 035 $a(EBL)3018991 035 $a(SSID)ssj0000418170 035 $a(PQKBManifestationID)11313447 035 $a(PQKBTitleCode)TC0000418170 035 $a(PQKBWorkID)10370884 035 $a(PQKB)11416403 035 $a(MiAaPQ)EBC3018991 035 $a(Au-PeEL)EBL3018991 035 $a(CaPaEBR)ebr10662797 035 $a(OCoLC)923659770 035 $a(BIP)18717607 035 $a(EXLCZ)992560000000069961 100 $a20080319d2009 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 00$aFrom problem toward solution $ewireless sensor networks security /$fZhen Jiang and Yi Pan, editors 205 $a1st ed. 210 $aNew York $cNova Science Publishers$dc2009 215 $a1 online resource (398 p.) 225 1 $aDistributed, cluster and grid computing 300 $aDescription based upon print version of record. 311 08$a1-60456-457-1 320 $aIncludes bibliographical references and index. 327 $aIntro -- FROM PROBLEM TOWARD SOLUTION:WIRELESS SENSOR NETWORKSSECURITY -- Distributed, Cluster and Grid Computing -- FROM PROBLEM TOWARD SOLUTION:WIRELESS SENSOR NETWORKSSECURITY -- CONTENTS -- PREFACE -- PART 1.ATTACKS AND COUNTERMEASURES -- PRESERVING DATA AUTHENTICITY IN WIRELESSSENSOR NETWORKS: ATTACKS ANDCOUNTERMEASURES -- Abstract -- 1. Introduction -- 2. Models and Approaches -- 2.1. System Model -- 2.2. Threat Model -- 2.3. Solution Approaches -- 3. Passive Approaches -- 3.1. Secure Report Generation -- 3.2. Filtering with Uniform Key Sharing -- 3.3. Filtering with Route-specific Key Sharing -- 3.3.1. Interleaved Hop-by-hop Authentication -- 3.3.2. Other Solutions with Route-specific Key Sharing -- 3.4. Filtering with Location-based Key Sharing -- 3.4.1. Location-Based Resilient Security -- 3.4.2. Location-aware End-to-End Data Security -- 4. Proactive Approaches -- 4.1. Group Re-keying -- 4.2. Packet Traceback -- 4.3. Correlation among Data Content -- 4.3.1. Correlation Analysis and Modified t-test -- 5. Conclusion -- References -- LOCATION TRACKING ATTACK IN AD HOCNETWORKS BASED ON TOPOLOGY INFORMATION -- Abstract -- 1. Introduction -- 2. RelatedWork -- 3. Localization Using Geometric Constraints -- 3.1. Constraint Solving Definitions -- 3.2. The Localization Algorithm -- 3.2.1. Phase 1-Deterministic Constraint Solving -- 3.2.2. Phase 2-Constraint Relaxation and Heuristic Improvements -- 3.3. Experimental Results -- 4. Localization Using DSR Protocol Information -- 4.1. Dynamic Source Routing -- 4.2. Scenario and Assumptions -- 4.3. Localization Approach -- 4.3.1. "Hop to Route Length Ratio" (HL) Heuristics -- 4.3.2. Derivation of Node Distribution along the Route from the HL Metric -- 4.3.3. Probability Based Position Estimation -- 4.4. Analysis -- 5. Conclusion -- Acknowledgement -- References. 327 $aPREVENTION OF DOS ATTACK IN SENSORNETWORKS USING REPEATED GAME THEORY -- Abstract -- 1. Introduction -- 2. RelatedWork -- 3. Game Formulation of the Proposed Protocol -- 3.1. Equilibrium -- 3.2. Payoff and Reputation -- 3.3. Protocol Description -- 4. Performance Evaluation -- 4.1. Metrics -- 4.2. Implementation -- References -- IMPACT OF PACKET INJECTION MODELSON MISBEHAVIOR DETECTION PERFORMANCEIN WIRELESS SENSOR NETWORKS -- Abstract -- 1. Introduction -- 1.1. Wireless Ad-Hoc Networks and the Concept of Misbehavior -- 1.2. Overview on Misbehavior in Wireless Ad-Hoc Networks -- 1.3. Intrusion Detection Systems - Detecting Misbehavior -- 1.4. Human Immune System - Inspiration for AIS -- 1.4.1. Adaptive Immune System -- 1.4.2. Innate Immune System -- 1.5. Translating Features of the HIS to AIS -- 2. Packet Injection Experiment - Problem Statement -- 2.1. Experimental Setup -- 2.2. Scenario Description -- 2.3. Network Topology -- 2.4. Node Misbehavior -- 2.5. Artificial Immune System - Details -- 3. Packet Injection Experiment - Results -- 4. AIS in Ad-Hoc Networks - RelatedWork -- 5. Conclusions and FutureWork -- Acknowledgments -- References -- PART 2.SECURED ROUTING AND LOCALIZATION -- SECURITY AWARE ROUTING IN HIERARCHICALOPTICAL SENSOR NETWORKS -- Abstract -- 1. Introduction -- 1.1. Motivation for Directional Optical Sensor Networks and Challenges -- 2. RelatedWork -- 3. Cluster-Based Directional Sensor Networks -- 3.1. Assumptions and Security Threat Model -- 4. The Security-Aware Base Station Circuit-Based Routing forCluster-based DOSN -- 4.1. Secure Neighborhood Discovery Protocol -- 5. Security Analysis -- 5.1. Per Hop Authentication and Alteration of Routing Beacons -- 5.2. Broadcast Authentication and Spoofed Routing Beacons -- 5.3. Beacon Freshness -- 6. Conclusion -- References -- SECURE MULTI-PATH DATA DELIVERY IN SENSORNETWORKS. 327 $aAbstract -- 1. Introduction -- 2. System Models -- 2.1. Network Model -- 2.2. Attack Model -- 3. Node-disjoint Multi-path Encoding/Decoding -- 3.1. Multi-path Source Routing Encoding -- 3.2. Multi-path Data Encoding -- 3.3. Multi-path Data Decoding -- 3.4. Communication Overhead -- 4. Path Selection -- 4.1. v(? 3)-node-disjoint Shortest Paths -- 4.2. Path Rating Algorithm -- 4.3. Path Selection Algorithm -- 5. Robustness Analysis -- 5.1. General Evaluation Formulas -- 5.2. Uniform Block Allocation and Uniform Success Probability Distribution -- 5.3. Evaluate Success Probability for Multi-path Routing -- 6. Conclusion -- Appendices -- A. Encoding of Reed-Solomon Codes -- B. Decoding of Reed-Solomon Codes -- C. Proof of (21) -- References -- SELOC: SECURE LOCALIZATION FOR WIRELESSSENSOR AND ACTOR NETWORK -- Abstract -- 1. Introduction -- 2. RelatedWork -- 3. Network Model -- 3.1. Attack Models -- 3.2. Features of Secure Localization -- 4. SeLoc Secure Scheme -- 4.1. Brief Review of SeLoc Scheme -- 4.2. SeLoc Scheme -- 4.3. Location Verification -- 5. Security Analysis -- 5.1. Robustness -- 5.2. Sensitivity of SeLoc Scheme -- 6. Conclusion -- References -- PART 3.CRYPTOGRAPHY AND ENCRYPTION -- SECURITY IN WIRELESS SENSOR NETWORKS:A FORMAL APPROACH? -- Abstract -- 1. Introduction -- 2. Model Checking for the Analysis of Security Protocols -- 3. Sensor Network Encryption Protocol: SNEP -- 4. Verification of SNEP -- 5. RelatedWork -- Security Network Protocols -- Simulators of Sensor Networks -- Analysis with Model Checking Techniques -- 6. Conclusion -- References -- C4W: AN ENERGY EFFICIENT PUBLIC KEYCRYPTOSYSTEM FOR LARGE-SCALE WIRELESSSENSOR NETWORKS -- Abstract -- 1. Introduction -- 1.1. Related Work -- 1.2. Contributions -- 2. Combined Public Key Scheme for Wireless Sensor Networks -- 2.1. Basic Scheme -- 2.2. Security-Enhanced Scheme (SES). 327 $a2.3. Protocol -- 3. Analysis -- 3.1. Security -- 3.2. Energy -- 4. Conclusion -- References -- ENERGY CONSUMPTION OF SECURITY ALGORITHMSIN WIRELESS SENSOR NODES -- Abstract -- 1. Introduction -- 2. Cryptographic Algorithms for WSN Nodes -- 2.1. New Method for Reorganization of Cryptographic Algorithms -- 2.2. Related Work -- 2.3. Verification of Results -- 3. Measurement of Energy Consumption for Security -- 3.1. Tradeoff between Security and Energy Consumption -- 3.2. Related Work -- 3.3. Measurement Techniques -- 3.4. Energy Consumption without Security -- 3.4.1. Measurements for CrossBow Nodes -- 3.4.2. Measurements for Ember Nodes -- 3.5. Energy Consumption for Security -- 3.5.1. Energy Consumption for Security in CrossBow Nodes -- 3.5.2. Energy Consumption for Security in Ember Nodes -- 3.5.3. Comparisons of CrossBow & -- Ember Nodes -- 4. Assessment of Life-Time Energy Consumption -- 4.1. Life Time Energy Consumption -- 4.2. Energy Measurements and Profile Analyzer -- 4.2.1. Operational Circuit -- 4.2.2. Measurement Record Program -- 4.2.3. E-Analyzer: Energy Profile Analyzer -- 4.3. Case Study: Security Algorithms in CrossBow MICA2 Nodes -- 5. Guidelines to Apply Security into WSN -- 6. Conclusions -- References -- PART 4.KEY PRE-DISTRIBUTION AND REVOCATION -- DETERMINISTIC AND RANDOMIZED KEYPRE-DISTRIBUTION SCHEMES FOR MOBILEAD-HOC NETWORKS: FOUNDATIONS ANDEXAMPLE CONSTRUCTIONS? -- Abstract -- 1. Introduction -- 2. General Considerations for Key Management Schemes -- 3. Techniques -- 3.1. Random Graph Based -- 4. Set System Based -- 4.0.1. Constrained Intersection Matrices -- 4.0.2. The BBR Polynomials -- 5. RandomWalk Based -- 5.1. Approximating the Evolution of Stochastic Processes -- 5.2. Gradual Increase of the Bit-Correlation -- 5.3. The General k-place Elimination Protocol -- 5.4. Assessment of the Elimination Protocol. 327 $a6. Probabilistic Technique Based -- 7. Conclusions -- References -- ARPD: ASYNCHRONOUS RANDOM KEYPREDISTRIBUTION IN THE LEAP FRAMEWORKFOR WIRELESS SENSOR NETWORKS -- Abstract -- 1. Introduction -- 2. RelatedWork -- 2.1. Pairwise Key Establishment in LEAP -- 2.1.1. LEAP Security -- 2.2. Random Pairwise Key Predistribution -- 3. ARPD for Node Additions -- 4. Performance Analysis -- 4.1. Section Notation and Assumptions -- 4.2. Probability of Connectivity -- 4.2.1. Key Reuse -- 4.2.2. Choice of Reuse Factor -- 5. Security Analysis -- 5.1. A Security Threat Model for WSNs -- 5.2. Outside Attacks -- 5.3. Inside Attacks -- 6. Conclusions -- References -- SECURE k-CONNECTIVITY PROPERTIESOF WIRELESS SENSOR NETWORKS -- Abstract -- 1. Introduction -- 2. The Reference Model -- 3. k-Connectivity of Kryptographs -- 3.1. Survivor Function Pr{connectivity ? k} -- 3.2. Expected Connectivity -- 4. Simulation Results -- 5. RelatedWork -- 6. Conclusion -- References -- GATEWAY SUBSET DIFFERENCE REVOCATION -- Abstract -- 1. Introduction -- 2. Subset Difference Revocation -- 3. Gateway Subset Difference Revocation -- 4. Evaluation -- 4.1. Security -- 4.2. Memory -- 4.3. Processing Load -- 5. Related Work -- 6. Conclusion -- References -- PART 5.KEY EXCHANGE AND ACCESS CONTROL -- AUTHENTICATED KEY EXCHANGE WITH GROUPSUPPORT FOR WIRELESS SENSOR NETWORKS -- Abstract -- 1. Introduction -- 1.1. Node-Compromise Attacker Model -- 1.2. Secure Link Communication -- 1.2.1. Random Key Pre-distribution -- 1.2.2. Pairwise Key Pre-distribution -- 1.3. Seed-Based Pre-distribution -- 1.3.1. Selective Node Capture Attack -- 1.3.2. Hypercube Pre-distribution -- 2. Group Supported Key Exchange -- 2.1. Authenticated Key Exchange with Group Support -- 2.2. Probabilistic Authentication -- 2.2.1. Probabilistic Authentication with Majority Decision. 327 $a2.3. Evaluation of the Communication and Computation Overhead. 330 $aReserving data authenticity in a hostile environment, where the sensor nodes may be compromised is a critical security issue for wireless sensor networks. This book covers location tracking attack in ad hoc networks based on topolgy information, security aware routing in hierarchical optical sensor networks and more. 410 0$aDistributed, cluster, and grid computing. 606 $aSensor networks$xSecurity measures 606 $aWireless LANs$xSecurity measures 606 $aWireless metropolitan area networks$xSecurity measures 606 $aAd hoc networks (Computer networks)$xSecurity measures 615 0$aSensor networks$xSecurity measures. 615 0$aWireless LANs$xSecurity measures. 615 0$aWireless metropolitan area networks$xSecurity measures. 615 0$aAd hoc networks (Computer networks)$xSecurity measures. 676 $a681/.25 701 $aJiang$b Zhen$01866371 701 $aPan$b Yi$f1960-$01646467 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910955382503321 996 $aFrom problem toward solution$94473763 997 $aUNINA