Dynamic Black List (DBL) algorithm to defense against DDoS attack in Vehicular Ad-hoc Network

A Vehicular Ad-hoc Network (VANET) is a group of vehicles, which have special equipments enable them to connect with each other as a wireless network .The attacks are considered as the most serious challenge against this network, especially those targeting availability requirement, which is one of the most important security requirements in VANET. The Denial of Service (DoS) and Distributed Denial of Service (DDoS) attacks are the most important attacks since they make the network not available for actual users. In this research, we present an algorithm to detect and face the DDoS attack. This algorithm depends on a black list contains the IDs for malicious vehicles, which are being chosen depending on a certain threshold value for a number of messages received from them. We analyze the algorithm performance depending on throughput, packet delivery ratio, end to end delay parameters, and compare it with the performance of the Queue Limiting Algorithm (QLA) .To achieve this purpose, we use NS2.35 simulator using details to support Wireless Access in Vehicular Environments (WAVE). The simulation results showed that the proposed algorithm reduces the effect of the attack Significantly since it increases the throughput and packet delivery ratio.