A Misbehavior-Based Reputation Management System for VANETs
Detecting misbehavior in vehicular ad-hoc networks is very important problem with wide range of implications including safety related and congestion avoidance applications. Most misbehavior detection schemes are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners. Because of rational behavior, it is more important to detect false information than to identify misbehaving nodes. In this paper, we propose a misbehavior-based reputation management system (MBRMS) which is composed of three components: misbehavior detection, event rebroadcast and global eviction algorithms, to detect and filter false data in vehicular ad-hoc networks (VANETs). The performance of MBRMS is evaluated through simulation. From the results of the simulation, we confirm that the proposed MBRMS identifies and evicts properly bad nodes by outlier detection method and misbehaving node risk value.
KeywordsEvent rebroadcast eviction algorithm misbehavior detection outlier detection reputation system VANETs
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