HC-TUS: Human Cognition-Based Trust Update Scheme for AI-Enabled VANET

作     者：Fang, Weidong Zhu, Chunsheng Guizani, Mohsen Rodrigues, Joel J. P. C. Zhang, Wuxiong 

作者机构：Chinese Acad Sci Sci & Technol Microsyst Lab Shanghai Inst Microsyst & Informat Technol Shanghai Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Shanghai Res & Dev Ctr Micronano Elect Shanghai Peoples R China Shenzhen Technol Univ Coll Big Data & Internet Shenzhen Peoples R China Mohamed Bin Zayed Univ Artificial Intelligence MBZ Machine Learning Dept Abu Dhabi U Arab Emirates Lusofona Univ COPELABS Lisbon Portugal 

出 版 物：《IEEE NETWORK》 (IEEE Network)

年 卷 期：2023年第37卷第5期

页      面：247-252页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Shanghai Natural Science Foundation [21ZR1461700] Brazilian National Council for Scientific and Technological Development-CNPq [313036/2020-9] 

主　　题：Vehicular ad hoc networks Artificial intelligence Computational modeling Security Trust management Blockchains Cognition Human factors Simulation Computer crime Artificial Intelligence (AI) Vehicular Ad Hoc Network (VANET) Trust Model Collusion Attack 

摘      要：Recently, Artificial Intelligence (AI) has received more attention for being used in many applications. It is expected to play a key role in Vehicular Ad Hoc Networks (VANET). On the other hand, AI-enabled VANET (AI-VANET) has become an emerging field. However, its cyber security is facing enormous challenges. Although many trust schemes are proposed for addressing these issues, the reliance on only trust updates could increase the risk of long-term attacks before being detected. In this article, we design a human cognition-based trust update scheme (HC-TUS) for AI-VANET. Significantly, the novel trust update scheme is designed by strategically incorporating the Ebbinghaus forgetting theory. The simulation results indicate that 1) HC-TUS could better meet the principle of & Ograve;Hard to get, easy to lose & Oacute;for trust than BRSN and BTDS;2) HC-TUS could detect and resist the collusion attack more quickly than BRSN and BTDS. The open issues in terms of trust for AI-VANET are also investigated and highlighted.