An Intelligent Game Theory based Intrusion Detection Framework and Enhanced Dolphin Swarm Algorithm (EDSA) based Cluster Head Election for Vehicle Security

Aasheesh Shukla and Himanshu Sharma

Vehicle ad hoc networks (referred as VANETs) have gained immense attention both from the industrial sector and academics, however, several challenges, especially, security is an essentiality that is susceptible to different kinds of network threats such as Black hole attack, Denial of Service (DoS), Sybil attack etc. Intrusion Detection System (IDS) is hailed to be one among the highly significant techniques designed for protecting network security in earlier literatures. But, the performance achieved of IDSs still requires improvement to follow the VANET scenario are extremely fast in moving and dynamic in behavior. Moreover, a non-static network topology, communicational expense and scalability during greater vehicular density are few of the other problems, which need to be dealt with when designing an IDS framework for VANETs. Also, this research work works towards mitigating these problems by presenting a game theory based intrusion detection approach and an Enhanced Dolphin Swarm Algorithm (EDSA) based clustering algorithm that can be used for VANET. Also, the communicational burden incurred in the IDS gets minimized with the use of a set of specification rules combined with an anomaly detection module for the detection of intrusive vehicles. At last, the newly introduced clustering algorithm helps in maintaining the IDS framework’s stability, which guarantees that the scalability of the framework is quite good for networks having extreme vehicular densities. The results of simulation reveal that the novel framework attains much better accuracy and rate of detection across an extensive group of attacks, when in parallel reduces the overall amount of intrusion detection associated traffic brought into the vehicular network.

Volume 11 | 11-Special Issue

Pages: 252-260

DOI: 10.5373/JARDCS/V11SP11/20192955