A Novel Security Approach for Data Flow And Data Pattern Analysis To Mitigate DDOS Attacks In VANETs

The VANET security is an important issue with the rise of the automatically driven vehicle based technologies. The automatically driven vehicle based clusters are programmed for each vehicle to run individually by coordinating with all of the other nodes in the VANET cluster. The proposed model has been designed to detect and mitigate the DoS and DDoS attacks in the VANET clusters to avoid any of the misbehavior or mis-happening in the form of VANET node failure, collision or in any other form. The DDoS attack prevention algorithm works as the real time attack detection and overhead data filtering algorithm in order to protect against the DoS and DDoS attacks. The proposed model result has been obtained on the basis of network load, throughput, packet delivery ratio, etc. The experimental results have proved the efficiency of the proposed model in comparison with the existing models.