A novel classifier exploiting mobility behaviors for Sybil detection in connected vehicle systems

Yang, Zhe, Zhang, Kuan, Lei, Lei, and Zheng, Kan (2019) A novel classifier exploiting mobility behaviors for Sybil detection in connected vehicle systems. IEEE Internet of Things Journal, 6 (2). pp. 2626-2636.

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A Sybil attacker is able to obtain more than one identities and disguise as multiple vehicles in order to interfere the normal operations of the Connected Vehicle System (CVS). In this paper, we propose a novel classifier to detect Sybil attackers according to their mobility behaviors. Specifically, three levels of Sybil attackers are first defined according to their attack abilities. Through analyzing the mobility behaviors of vehicles, a learning-based model is used in the Central Server (CS) to extract mobility features and distinguish Sybil attackers from benign vehicles. Three classification algorithms are tested and compared, i.e., the Naive Bayes, Decision Tree, and Support Vector Machine. Furthermore, location certificates issued by Base Stations are used to resist location forgery by attackers. Based on the location certificates, the CS is able to evaluate the credibilities of uploaded locations using the Subjective Logic theory. In addition, we develop an edge betweenness-based community detection algorithm to handle the collusion among multiple Sybil attackers. Simulations are conducted based on a real-world vehicle trajectory dataset, which indicate that the proposed scheme is effective to resist Sybil attackers in CVS.

Item ID: 57446
Item Type: Article (Research - C1)
ISSN: 2327-4662
Keywords: peer-to-peer computing; cryptography; public transportation; feature extraction; trajectory; social network services; receivers; Sybil attack; connected vehicle system; vehicle mobility; machine learning
Copyright Information: (c) 2018 IEEE.
Funders: National Natural Science Foundation of China (NSFC), Beijing University of Posts and Telecommunications (BUPT)
Projects and Grants: NSFC Grant 61731004, BUPT Grant CX2016208
Date Deposited: 26 Mar 2019 01:42
FoR Codes: 40 ENGINEERING > 4006 Communications engineering > 400608 Wireless communication systems and technologies (incl. microwave and millimetrewave) @ 100%
SEO Codes: 89 INFORMATION AND COMMUNICATION SERVICES > 8901 Communication Networks and Services > 890103 Mobile Data Networks and Services @ 100%
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