LEADER 08889nam 2200589 450 001 9910830597903321 005 20240219153256.0 010 $a1-119-08216-1 010 $a1-119-08215-3 010 $a1-119-08214-5 024 7 $a10.1002/9781119082163 035 $a(CKB)3710000000503529 035 $a(EBL)4040964 035 $a(MiAaPQ)EBC4040964 035 $a(MiAaPQ)EBC1895375 035 $a(CaBNVSL)mat07159544 035 $a(IDAMS)0b00006484920710 035 $a(IEEE)7159544 035 $a(PPN)189716312 035 $a(EXLCZ)993710000000503529 100 $a20151229d2015 uy 101 0 $aeng 135 $aur|n|---||||| 181 $2rdacontent 182 $2rdamedia 183 $2rdacarrier 200 10$aVehicular ad hoc network security and privacy /$fXiaodong Lin, Rongxing Lu 210 1$aHoboken [New Jersey] :$cIEEE Press/Wiley,$d[2015] 210 2$a[Piscataqay, New Jersey] :$cIEEE Xplore,$d[2015] 215 $a1 online resource (237 p.) 225 1 $aIEEE press series on information and communication networks security 225 1 $aIEEE Press series on information & communication networks security 300 $aDescription based upon print version of record. 311 $a1-118-91390-6 320 $aIncludes bibliographical references at the end of each chapters and index. 327 $aList of Figures xi -- List of Tables xv -- Acronyms xvii -- Preface xix -- 1 INTRODUCTION 1 -- 1.1 Background 1 -- 1.2 DSRC AND VANET 2 -- 1.2.1 DSRC 2 -- 1.2.2 VANET 3 -- 1.2.3 Characteristics of VANET 6 -- 1.3 Security and Privacy Threats 7 -- 1.4 Security and Privacy Requirements 8 -- 1.5 Challenges and Prospects 9 -- 1.5.1 Conditional Privacy Preservation in VANETs 9 -- 1.5.2 Authentication with Efficient Revocation in VANETs 10 -- 1.6 Standardization and Related Activities 11 -- 1.7 Security Primitives 13 -- 1.8 Outline of the Book 17 -- References 17 -- 2 GSIS: GROUP SIGNATURE AND ID-BASED SIGNATURE-BASED SECURE AND PRIVACY-PRESERVING PROTOCOL 21 -- 2.1 Introduction 21 -- 2.2 Preliminaries and Background 23 -- 2.2.1 Group Signature 23 -- 2.2.2 Bilinear Pairing and ID-Based Cryptography 23 -- 2.2.3 Threat Model 23 -- 2.2.4 Desired Requirements 24 -- 2.3 Proposed Secure and Privacy-Preserving Protocol 25 -- 2.3.1 Problem Formulation 25 -- 2.3.2 System Setup 27 -- 2.3.3 Security Protocol between OBUs 29 -- 2.3.4 Security Protocol between RSUs and OBUs 38 -- 2.4 Performance Evaluation 41 -- 2.4.1 Impact of Traffic Load 43 -- 2.4.2 Impact of Cryptographic Signature Verification Delay 43 -- 2.4.3 Membership Revocation and Tracing Efficiency 45 -- 2.5 Concluding Remarks 47 -- References 47 -- 3 ECPP: EFFICIENT CONDITIONAL PRIVACY PRESERVATION PROTOCOL 51 -- 3.1 Introduction 51 -- 3.2 System Model and Problem Formulation 52 -- 3.2.1 System Model 52 -- 3.2.2 Design Objectives 54 -- 3.3 Proposed ECPP Protocol 55 -- 3.3.1 System Initialization 55 -- 3.3.2 OBU Short-Time Anonymous Key Generation 56 -- 3.3.3 OBU Safety Message Sending 62 -- 3.3.4 OBU Fast Tracking Algorithm 63 -- 3.4 Analysis on Conditional Privacy Preservation 64 -- 3.5 Performance Analysis 66 -- 3.5.1 OBU Storage Overhead 66 -- 3.5.2 OBU Computation Overhead on Verification 66 -- 3.5.3 TA Computation Complexity on OBU Tracking 68 -- 3.6 Concluding Remarks 69 -- References 69 -- 4 PSEUDONYM-CHANGING STRATEGY FOR LOCATION PRIVACY 71. 327 $a4.1 Introduction 71 -- 4.2 Problem Definition 73 -- 4.2.1 Network Model 73 -- 4.2.2 Threat Model 74 -- 4.2.3 Location Privacy Requirements 75 -- 4.3 Proposed PCS Strategy for Location Privacy 75 -- 4.3.1 KPSD Model for PCS Strategy 75 -- 4.3.2 Anonymity Set Analysis for Achieved Location Privacy 79 -- 4.3.3 Feasibility Analysis of PCS Strategy 85 -- 4.4 Performance Evaluation 86 -- 4.5 Concluding Remarks 89 -- References 89 -- 5 RSU-AIDED MESSAGE AUTHENTICATION 91 -- 5.1 Introduction 91 -- 5.2 System Model and Preliminaries 93 -- 5.2.1 System Model 93 -- 5.2.2 Assumption 93 -- 5.2.3 Problem Statement 94 -- 5.2.4 Security Objectives 95 -- 5.3 Proposed RSU-Aided Message Authentication Scheme 96 -- 5.3.1 Overview 96 -- 5.3.2 Mutual Authentication and Key Agreement between RSUs and Vehicles 96 -- 5.3.3 Hash Aggregation 98 -- 5.3.4 Verification 99 -- 5.3.5 Privacy Enhancement 100 -- 5.4 Performance Evaluation 101 -- 5.4.1 Message Loss Ratio 102 -- 5.4.2 Message Delay 102 -- 5.4.3 Communication Overhead 104 -- 5.5 Security Analysis 105 -- 5.6 Concluding Remarks 106 -- References 107 -- 6 TESLA-BASED BROADCAST AUTHENTICATION 109 -- 6.1 Introduction 109 -- 6.2 Timed Efficient and Secure Vehicular Communication Scheme 110 -- 6.2.1 Preliminaries 110 -- 6.2.2 System Formulation 112 -- 6.2.3 Proposed TSVC Scheme 113 -- 6.2.4 Enhanced TSVC with Nonrepudiation 118 -- 6.2.5 Discussion 123 -- 6.3 Security Analysis 129 -- 6.4 Performance Evaluation 129 -- 6.4.1 Impact of Vehicle Moving Speed 131 -- 6.4.2 Impact of Vehicle Density 132 -- 6.5 Concluding Remarks 134 -- References 134 -- 7 DISTRIBUTED COOPERATIVE MESSAGE AUTHENTICATION 137 -- 7.1 Introduction 137 -- 7.2 Problem Formulation 138 -- 7.2.1 Network Model 138 -- 7.2.2 Security Model 139 -- 7.3 Basic Cooperative Authentication Scheme 140 -- 7.4 Secure Cooperative Authentication Scheme 141 -- 7.4.1 Evidence and Token for Fairness 142 -- 7.4.2 Authentication Proof 145 -- 7.4.3 Flows of Proposed Scheme 146 -- 7.5 Security Analysis 147. 327 $a7.5.1 Linkability Attack 147 -- 7.5.2 Free-Riding Attack without Authentication Efforts 147 -- 7.5.3 Free-Riding Attack with Fake Authentication Efforts 148 -- 7.6 Performance Evaluation 148 -- 7.6.1 Simulation Settings 148 -- 7.6.2 Simulation Results 149 -- 7.7 Concluding Remarks 150 -- References 151 -- 8 CONTEXT-AWARE COOPERATIVE AUTHENTICATION 153 -- 8.1 Introduction 153 -- 8.2 Message Trustworthiness in VANETs 156 -- 8.3 System Model and Design Goal 159 -- 8.3.1 Network Model 159 -- 8.3.2 Attack Model 159 -- 8.3.3 Design Goals 160 -- 8.4 Preliminaries 160 -- 8.4.1 Pairing Technique 160 -- 8.4.2 Aggregate Signature and Batch Verification 160 -- 8.5 Proposed AEMAT Scheme 161 -- 8.5.1 System Setup 161 -- 8.5.2 Registration 162 -- 8.5.3 SER Generation and Broadcasting 162 -- 8.5.4 SER Opportunistic Forwarding 162 -- 8.5.5 SER Aggregated Authentication 163 -- 8.5.6 SER Aggregated Trustworthiness 165 -- 8.6 Security Discussion 168 -- 8.6.1 Collusion Attacks 168 -- 8.6.2 Privacy Protection of Witnesses 168 -- 8.7 Performance Evaluation 169 -- 8.7.1 Transmission Cost 169 -- 8.7.2 Computational Cost 169 -- 8.8 Concluding Remarks 170 -- References 170 -- 9 FAST HANDOVER AUTHENTICATION BASED ON MOBILITY PREDICTION 173 -- 9.1 Introduction 173 -- 9.2 Vehicular Network Architecture 175 -- 9.3 Proposed Fast Handover Authentication Scheme Based on Mobility Prediction 176 -- 9.3.1 Multilayer Perceptron Classifier 176 -- 9.3.2 Proposed Authentication Scheme 178 -- 9.4 Security Analysis 183 -- 9.4.1 Replay Attack 183 -- 9.4.2 Forward Secrecy 183 -- 9.5 Performance Evaluation 184 -- 9.6 Concluding Remarks 185 -- References 186 -- Index 187. 330 $aUnlike any other book in this area, this book provides innovative solutions to security issues, making this book a must read for anyone working with or studying security measures. Vehicular Ad Hoc Network Security and Privacy mainly focuses on security and privacy issues related to vehicular communication systems. It begins with a comprehensive introduction to vehicular ad hoc network and its unique security threats and privacy concerns and then illustrates how to address those challenges in highly dynamic and large size wireless network environments from multiple perspectives. This book is richly illustrated with detailed designs and results for approaching security and privacy threats. Additional features of this book include: . An introduction to standardization and industry activities as well as government regulation in secure vehicular networking. Eight novel secure and privacy-preserving schemes for vehicular communications. Explorations into interdisciplinary methods by combining social science, cryptography, and privacy enhancing technique The authors have taken a non-traditional method toward securing communications, allowing for new research directions in security and privacy in VANETs, which will be helpful to students, researchers, and IT practitioners. 410 0$aIEEE Press series on information & communication networks security. 606 $aVehicular ad hoc networks (Computer networks) 615 0$aVehicular ad hoc networks (Computer networks) 676 $a388.312 700 $aLin$b Xiaodong$0881835 702 $aLu$b Rongxing 801 0$bCaBNVSL 801 1$bCaBNVSL 801 2$bCaBNVSL 906 $aBOOK 912 $a9910830597903321 996 $aVehicular ad hoc network security and privacy$94028196 997 $aUNINA LEADER 03211nam 22005655 450 001 9910422644603321 005 20250610110324.0 010 $a9783030483593 010 $a3030483592 024 7 $a10.1007/978-3-030-48359-3 035 $a(CKB)4100000011435745 035 $a(MiAaPQ)EBC6348297 035 $a(DE-He213)978-3-030-48359-3 035 $a(PPN)259351407 035 $a(Perlego)3480818 035 $a(MiAaPQ)EBC29092743 035 $a(EXLCZ)994100000011435745 100 $a20200909d2020 u| 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aExtinction Rebellion and Climate Change Activism $eBreaking the Law to Change the World /$fby Oscar Berglund, Daniel Schmidt 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Palgrave Macmillan,$d2020. 215 $a1 online resource (VIII, 109 p. 1 illus.) 311 08$a9783030483586 311 08$a3030483584 327 $a1. Introduction -- 2. XR and Anarchism -- 3. Civility and Disobedience -- 4. Between Democracy and Efficiency -- 5. Reimagining Democracy -- 6. A Theory of Change: The Civil Resistance Model -- 7. Conclusion: XR, The Climate Change Movement and Capitalism. . 330 $aThis book summarises and critiques Extinction Rebellion (XR) as a social movement organisation, engaging with key issues surrounding its analysis, strategy and tactics. The authors suggest that XR have an underdeveloped and apolitical view of the kind of change necessary to address climate change, and suggest that while this enables the building of broad movements, it is also an obstacle to achieving the systemic change that they are aiming for. The book analyses different forms of protest and the role of civil disobedience in their respective success or failure; democratic demands and practices; and activist engagement with the political economy of climate change. It engages with a range of theoretical perspectives that address law-breaking in protest and participatory forms of democracy including liberal political theory; anarchism and forms of historical materialism, and will be of interest to students and scholars across politics, international relations, sociology, policystudies and geography, as well as those interested in climate change politics and activism. Oscar Berglund is Lecturer in International Public and Social Policy at the University of Bristol, UK. Daniel Schmidt is a MSc graduate in Public Policy from the University of Bristol, UK. 606 $aPolitical sociology 606 $aEnvironmental policy 606 $aPolitical Sociology 606 $aEnvironmental Policy 615 0$aPolitical sociology. 615 0$aEnvironmental policy. 615 14$aPolitical Sociology. 615 24$aEnvironmental Policy. 676 $a551.6 676 $a300 700 $aBerglund$b Oscar$0861271 702 $aSchmidt$b Daniel 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910422644603321 996 $aExtinction rebellion and climate change activism$91922201 997 $aUNINA LEADER 04564nam 22006495 450 001 9910743356503321 005 20251113203755.0 010 $a981-16-6166-9 010 $a981-16-6165-0 010 $a981-16-6166-9 024 7 $a10.1007/978-981-16-6166-2 035 $a(MiAaPQ)EBC6876633 035 $a(Au-PeEL)EBL6876633 035 $a(CKB)21028245100041 035 $a(PPN)269154809 035 $a(OCoLC)1298387696 035 $a(DE-He213)978-981-16-6166-2 035 $a(EXLCZ)9921028245100041 100 $a20220130d2022 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aHeterogeneous Graph Representation Learning and Applications /$fby Chuan Shi, Xiao Wang, Philip S. Yu 205 $a1st ed. 2022. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2022. 215 $a1 online resource (329 pages) 225 1 $aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 311 08$aPrint version: Shi, Chuan Heterogeneous Graph Representation Learning and Applications Singapore : Springer Singapore Pte. Limited,c2022 9789811661655 320 $aIncludes bibliographical references. 327 $aIntroduction -- The State-of-the-art of Heterogeneous Graph Representation -- Part One: Techniques -- Structure-preserved Heterogeneous Graph Representation -- Attribute-assisted Heterogeneous Graph Representation -- Dynamic Heterogeneous Graph Representation -- Supplementary of Heterogeneous Graph Representation -- Part Two: Applications -- Heterogeneous Graph Representation for Recommendation -- Heterogeneous Graph Representation for Text Mining -- Heterogeneous Graph Representation for Industry Application -- Future Research Directions -- Conclusion. . 330 $aRepresentation learning in heterogeneous graphs (HG) is intended to provide a meaningful vector representation for each node so as to facilitate downstream applications such as link prediction, personalized recommendation, node classification, etc. This task, however, is challenging not only because of the need to incorporate heterogeneous structural (graph) information consisting of multiple types of node and edge, but also the need to consider heterogeneous attributes or types of content (e.g. text or image) associated with each node. Although considerable advances have been made in homogeneous (and heterogeneous) graph embedding, attributed graph embedding and graph neural networks, few are capable of simultaneously and effectively taking into account heterogeneous structural (graph) information as well as the heterogeneous content information of each node. In this book, we provide a comprehensive survey of current developments in HG representation learning. Moreimportantly, we present the state-of-the-art in this field, including theoretical models and real applications that have been showcased at the top conferences and journals, such as TKDE, KDD, WWW, IJCAI and AAAI. The book has two major objectives: (1) to provide researchers with an understanding of the fundamental issues and a good point of departure for working in this rapidly expanding field, and (2) to present the latest research on applying heterogeneous graphs to model real systems and learning structural features of interaction systems. To the best of our knowledge, it is the first book to summarize the latest developments and present cutting-edge research on heterogeneous graph representation learning. To gain the most from it, readers should have a basic grasp of computer science, data mining and machine learning. 410 0$aArtificial Intelligence: Foundations, Theory, and Algorithms,$x2365-306X 606 $aData mining 606 $aMachine learning 606 $aArtificial intelligence$xData processing 606 $aData Mining and Knowledge Discovery 606 $aMachine Learning 606 $aData Science 615 0$aData mining. 615 0$aMachine learning. 615 0$aArtificial intelligence$xData processing. 615 14$aData Mining and Knowledge Discovery. 615 24$aMachine Learning. 615 24$aData Science. 676 $a511.5 700 $aShi$b Chuan$0964112 702 $aWang$b Xiao 702 $aYu$b Philip S. 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910743356503321 996 $aHeterogeneous graph representation learning and applications$93558732 997 $aUNINA