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A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET
Author(s) -
P. Remya Krishnan,
P. Arun Raj Kumar
Publication year - 2021
Publication title -
international journal of communication systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.344
H-Index - 49
eISSN - 1099-1131
pISSN - 1074-5351
DOI - 10.1002/dac.4621
Subject(s) - sybil attack , computer science , vehicular ad hoc network , node (physics) , computer network , wireless ad hoc network , intelligent transportation system , heuristic , computer security , wireless , wireless sensor network , telecommunications , artificial intelligence , civil engineering , structural engineering , engineering
Summary Vehicular ad hoc network (VANET) is a part of the intelligent transportation system (ITS) that provides safety and nonsafety applications. The high mobility of vehicles and the wireless communication environment in VANET makes it vulnerable to various attacks. One among them is the Sybil attack, where a Sybil attacker creates multiple fake identities called Sybil nodes that disrupt the functionality of VANET. Most of the existing solutions in the literature discuss identifying the Sybil nodes (virtual); very few works exist to determine the Sybil attacker (source node that generates Sybil nodes). In this paper, we propose a computation less heuristic approach that focuses on detecting the Sybil attacker and its Sybil nodes using signal strength measurements and Euclidean distance as the detection parameters. The central VANET server, Road Side Units (RSUs), and vehicles collaborate in the detection process, which improves the accuracy of our approach. The core of the approach is a reward‐based system, where the vehicle rewards are determined by collecting RSUs' feedback about the vehicle behavior. From simulation experiments, it is evident that our proposed approach achieves a maximum detection rate of 99.89% and a false positive rate of 0.012% than the existing techniques.