RETRACTED ARTICLE: Optimal Hop Selection Based Novel Trust Based DDoS Attack Removal Framework for Reliable and Secured Transmission of Data in VANETs

Abstract

This paper proposes a new Trust based DDoS Attack Removal Framework (T-DARF) for effective trust management in VANETs. Based on a newly developed data centric validation unit and intrusion detection unit, all the misbehaving nodes are removed and allows the framework to prevent DDoS attacks in a distributed and collaborative manner. In other words, our proposed framework ensures a trusted, reliable communication between vehicles and delivering reduced network overhead by handling the DDoS attacks. T-DARF is built of three elements: (1) for the detection of dishonest nodes it includes a collaborative and distributed elements, (2) to filter the malicious data it includes a data-centric validation element, and (3) a delay checking element for the detection and prevention against DoS and DDoS attacks. Also, a new trust-based routing protocol is developed that uses the idea of companions (i.e. integrating the notions of link quality and trust value of neighbors) to select the trusted vehicles and to select the optimal path we imposed a hybrid Dragonfly based particle swarm optimization (DPSO) algorithm. The simulation results proved the efficiency of our proposed trust based framework on detecting dishonest nodes, the malicious data transmitted by the honest/dishonest nodes and also detecting the colluding attacks that destroys the network resources in a short period. Also, T-DARF in a worst case scenario can sustain its performance degrees and outperforms the effectiveness of existing schemes such as TRIP, AECFV and T-CLAIDS.