Attack models and infrastructure supported detection mechanisms for position forging attacks in vehicular ad hoc networks

Abstract

Vehicular ad hoc networks (VANETs) are vulnerable to message forging attacks, where an attacker creates a new message or replays/modifies an existing message. Forging of message can be carried out by attacker directly or indirectly through another vehicle. In VANETs, each vehicle periodically broadcasts short packets (beacons) with its identifier, time and current geographical position. In a position forging attack, an attacker broadcasts timely coordinated traffic warning messages with forged positions, producing illusion of an accident/traffic jam or an emergency braking. In this manner, VANET performance degrades in terms of channel utilization. It also severely impact the performance of security algorithms. In this paper, our focus is on the design and implementation of various forms of position forging attacks. We have presented detection approaches for these attacks. Unlike existing detection approaches, our methods are not based on the concept of estimating the position of senders. We have analyzed the impact of forged position information on average vehicle speed, number of collisions and percentage of delivered packets. Effectiveness of detection methods for various attack scenarios is compared. Instead, it works on the pattern of position information broadcast in consecutive packets. Simulation results demonstrates the effectiveness and adaptability of our proposed approach for VANETs.