. Predict and prevent from misbehaving intruders in heterogeneous vehicular networks. Vehicular Communications, Elsevier, 2017, 10, pp.74-83. <10.1016/j.vehcom.2016 ). The purpose of HetVNet is ensuring a wide area coverage to all vehicles in a large scale network, thus achieving the Always Best Connected (ABC) paradigm where the best continuous connectivity is offered to clients. In addition, HetVNet enables the acquisition and processing of a large amount of data from wide geographical areas via smart vehicles to offer various categories of services to drivers and passengers. There are many challenges in HetVNet and security is one of them since, in one hand, vehicles exchange vital data (about congestions, accidents, hazards, road-works, etc.) and in the other hand they form a specific network with particular characteristics (frequent fragmentation, dynamic topology, no centralized authority, etc.). Intrusion detection systems (IDS) act as a second wall of defense when cryptography is broken and already proved their effectiveness against both external and internal intruders. Therefore, in this research work we propose and implement an intrusion detection and prediction scheme able to detect and especially predict the future misbehavior of a malicious vehicle. The attack prediction technique proposed in this paper is based on a game theory to prevent the occurrence of malicious vehicles. Moreover, the proposed detection scheme detects the most dangerous attacks that target a HetVNet such as false alerts and Sybil attacks. This detection uses a rules-based technique to model a normal behavior of a vehicle. Simulations performed using NS-3 show that our scheme exhibits a high accuracy prediction, faster attack detection, and a low communication overhead compared to current detection frameworks.
In REF , an intrusion detection and prediction scheme has proposed to detect and especially predict the future misbehavior of a malicious vehicle.
Predict and prevent from misbehaving intruders in heterogeneous vehicular networks
Veh. Commun.
Veh. Commun.
Computer Science