Jamming Attack in Vehicular Networks: Adaptively Probabilistic Channel Surfing Scheme

Abstract

Vehicular networks play a crucial role in Intelligent Transportation System (ITS), making transportation safer and more convenient. Most applications in ITS require information carried by basic safety messages (BSMs) to be exchanged periodically among vehicles. However, BSMs are vulnerable to different attacks, especially jamming attacks, due to their limited short message length and life span. In this paper, we analyze the impact of a jamming attack on BSMs and initially propose a random channel surfing scheme to attempt to react to the attack. We investigate the scheme by a simple extendible probabilistic model and simulation in NS-3. Obtained results provide a reference to design an optimal channel surfing scheme that adapts to its supported applications.