Security in Vehicular Networks

Leila Benarous is an associate professor in the Computer Science department and a researcher at LIM Laboratory, University of Laghouat, Algeria. She is also an associate member of UPEC-LiSSi-TincNET Research Team, France.Salim Bitam is a professor of Computer Science and vice rector responsible for post-graduation training and scientific research at the University of Biskra, Algeria. His main research interests include vehicular networks, cloud computing and bio-inspired methods.Abdelhamid Mellouk is currently the director of IT4H High School Engineering Department, a professor at the University of Paris-Est Créteil (UPEC) and Head of UPEC-LiSSi-TincNET Research Team, France. He is the founder of the Network Control Research and Curricula activities in UPEC, the current co President of the French Deep Tech Data Science and Artificial Intelligence Systematic Hub, member of the Algerian High Research Council (CNRST) and an associate editor of several top ranking scientific journals.

• Preface xiList of Acronyms xiiiIntroduction xixChapter 1 Vehicular Networks 11.1 Introduction 11.2 Motivation by numbers 21.3 Evolution 31.4 Architecture 41.5 Characteristics 51.6 Technical challenges and issues 61.7 Wireless technology 71.8 Standards 71.8.1 IEEE WAVE stack 81.8.2 ETSI standards 91.8.3 The 3GPP standard 91.9 Types 101.9.1 The autonomous vehicle (self-dependent) 101.9.2 VANET 111.9.3 Vehicular clouds 111.9.4 Internet of vehicles 121.9.5 Social Internet of vehicles 141.9.6 Data named vehicular networks 151.9.7 Software-defined vehicular networks 151.10 Test beds and real implementations 161.11 Services and applications 171.12 Public opinion 191.13 Conclusion 20Chapter 2 Privacy and Security in Vehicular Networks 212.1 Introduction 212.2 Privacy issue in vehicular networks 222.2.1 Types 232.2.2 When and how it is threatened? 242.2.3 Who is the threat? 242.2.4 What are the consequences? 242.2.5 How can we protect against it? 252.3 State-of-the-art location privacy-preserving solutions 282.3.1 Non-cooperative change 282.3.2 Silence approaches 282.3.3 Infrastructure-based mix-zone approach 282.3.4 The cooperation approach (distributed mix-zone) 362.3.5 Hybrid approach 362.4 Authentication issues in vehicular networks 492.4.1 What is being authenticated in vehicular networks? 492.4.2 Authentication types 502.4.3 How does authentication risk privacy? 512.5 Identity privacy preservation authentication solutions: state of the art 522.6 Conclusion 54Chapter 3 Security and Privacy Evaluation Methodology 553.1 Introduction 553.2 Evaluation methodology 583.2.1 Security 583.2.2 Privacy 663.3 Conclusion 74Chapter 4 The Attacker Model 754.1 Introduction 754.2 Security objectives 764.3 Security challenges 784.4 Security attacker 794.4.1 Aims 804.4.2 Types 804.4.3 Means 814.4.4 Attacks 82Contents vii4.4.5 Our attacker model 854.5 Conclusion 90Chapter 5 Privacy-preserving Authentication in Cloud-enabled Vehicle Data Named Networks (CVDNN) for Resources Sharing 915.1 Introduction 915.2 Background 925.2.1 Vehicular clouds 925.2.2 Vehicular data named networks 945.3 System description 945.4 Forming cloud-enabled vehicle data named networks 955.5 Migrating the local cloud virtual machine to the central cloud 975.6 Privacy and authentication when using/providing CVDNN services 975.6.1 The authentication process 985.6.2 The reputation testimony 1005.7 The privacy in CVDNN 1025.8 Discussion and analysis 1035.8.1 The privacy when joining the VC 1035.8.2 Privacy while using the VC 1065.9 Conclusion 106Chapter 6 Privacy-preserving Authentication Scheme for On-road On-demand Refilling of Pseudonym in VANET 1096.1 Introduction 1096.2 Network model and system functionality 1116.2.1 Network model 1116.2.2 The system functionality 1136.3 Proposed scheme 1146.4 Analysis and discussion 1196.4.1 Security analysis 1196.4.2 Burrows, Abadi and Needham (BAN) logic 1246.4.3 SPAN and AVISPA tools 1266.5 Conclusion 129Chapter 7 Preserving the Location Privacy of Vehicular Ad hoc Network Users 1317.1 Introduction 1317.2 Adversary model 1337.3 Proposed camouflage-based location privacy-preserving scheme 1337.3.1 Analytical model 1357.3.2 Simulation 1367.4 Proposed hybrid pseudonym change strategy 1417.4.1 Hypothesis and assumptions 1417.4.2 Changing the pseudonyms 1427.4.3 The simulation 1457.5 Conclusion 148Chapter 8 Preserving the Location Privacy of Internet of Vehicles Users 1518.1 Introduction 1518.2 CE-IoV 1538.3 Privacy challenges 1568.4 Attacker model 1578.5 CLPPS: cooperative-based location privacy-preserving scheme for Internet of vehicles 1588.5.1 Simulation 1598.5.2 Comparative study and performance analysis 1638.6 CSLPPS: concerted silence-based location privacy-preserving scheme for Internet of vehicles 1668.6.1 The proposed solution 1668.6.2 Simulation results 1678.6.3 Comparative study performance analysis 1698.7 Obfuscation-based location privacy-preserving scheme in cloud-enabled Internet of vehicles 1718.7.1 The proposition 1718.7.2 Study of feasibility using game theoretic approach 1738.7.3 The simulation 1748.7.4 Analytical model 1778.7.5 Comparative study 1788.8 Conclusion 180Chapter 9 Blockchain-based Privacy-aware Pseudonym Management Framework for Vehicular Networks 1819.1 Introduction 1819.2 Background 1839.2.1 Public key infrastructure (PKI) 1839.2.2 Vehicular PKI 1859.2.3 Blockchain technology 1859.2.4 Blockchain of blockchains 1909.3 Related works 1919.3.1 Blockchain-based PKI 1919.3.2 Privacy-aware blockchain-based PKI 1919.3.3 Monero 1919.3.4 Blockchain-based vehicular PKI 1929.4 Key concepts 1929.4.1 Ring signature 1929.4.2 One-time address 1949.5 Proposed solution 1959.5.1 General description 1959.5.2 Registration to the blockchain 1969.5.3 Certifying process 1969.5.4 Revocation process 1979.5.5 Transaction structure and validation 1979.5.6 Block structure and validation 2009.5.7 Authentication using blockchain 2019.6 Analysis 2029.7 Comparative study 2069.8 Conclusion 206Conclusion 211References 215Index 229