Abstract:
Vehicular Ad Hoc Network systems are the type of MANETs in which vehicles nodes made up the whole network. These networks are used for improvement in traffic safety systems. Keeping in view the benefits of these networks, vast research has been carried out in the past to address the security issues. Among other attacks, black hole attack is one of the most vulnerable attacks in vehicular ad hoc networks that results in the network performance degradation. In black hole attack, the basic aim of the malicious node is to send fake route reply packets to source node by attracting source node that it has the shortest path to the destination where actually when the actual data transmission starts, it doesn't forward the packets and simply drops them. In the past, research has been conducted to propose an effective and efficient technique to detect black hole attack in Vanets. Most of the solutions are only workable in single black hole attack, but not suitable for multiple nodes black hole attack. Also, most of the proposed solutions have limitations in terms of the average end- to- end delay and mobility. Previous studies have shown that cooperative monitoring schemes can be helpful to detect selfish nodes in the network. Previous studies on analyzing the packet drop ratio, average end to end delay and network throughput employed Intrusion Detection Systems.
In this study, we have proposed a hybrid approach based on AODV protocol to provide a solution for detection of black hole attack in the network. We have employed Trust Management and Fuzzy Logic Analyzer to more accurately detect the black hole attack in Vanets. Our simulation results show that the proposed mechanism is more effective and accurate in detecting black hole attack. The results are benchmarked against published data and closely match the expected outcome. The proposed approach is the significant improvement towards better detection of black hole attack.
