Abstract
Smart technologies have seeped into every aspect of human communication. The increase in population has escalated the number of vehicles on road as well as probability of collisions. Development of intelligent vehicles for improving driver experience have introduced the Mobile Ad hoc Technologies into transport systems in the form of Vehicular Ad hoc Networks (VANETs), also known as the Inter Vehicular Communication Network. This is an intrinsically wireless system with a set of security challenges that are inherently dependent on its lack of infrastructure, short connection times and high mobility. VANETs aim to provide users with optimum driving experience as well as safety on road. The most significant service for the vehicular networks is the availability of ubiquitous information to the legitimate users because a delay in this life-critical and time-sensitive network can be fatal in some scenarios. Hence, Denial of Service (DoS) is one of the most imminent security threat for this system. Although, some research has been done for the mitigation of this issue, data mining has not been optimally applied to solve it. Moreover, the available schemes are deficient in one aspect or the other in order to provide impeccable detection. The capability of decision tree classification to timely identify behavioral changes in traffic with low error rate makes it a powerful detection scheme. This paper describes the characteristics of VANETs and aims to identify the most critical types of DoS attacks on vehicular networks. Furthermore, it comprehensively reviews available solutions in current literature for mitigating this attack on Inter Vehicular Communications. The paper also discusses some of the future challenges for security in VANETs.