Prevention of Rushing Attack in AOMDV using Random Route Selection Technique in Mobile Ad-hoc Network

Ad Hoc Network is wireless networks that get more attention from past to present. Mobile ad hoc network (MANET) is one of the types of ad hoc networks, it deployed rapidly because it infrastructure-less. Node in mobile ad hoc network communicates through wireless links without wired channels. When source nodes want to communicate with the destination outside its transmission range it uses multi-hop mechanisms. Intermediate node forwards the data packet to the next node until the data packet reaches destinations. Due wireless links and lack of centralized administration device, mobile ad hoc network is more vulnerabile for security attacks. Rushing attack is one of the most dangerous attacks in the on-demand routing protocol of mobile ad hoc networks. Rushing attack highly transmit route request with higher transmission power than the genuine nodes and become participate between source and destination nodes, after that it delay or drop actual data pass through it. In this study, the researcher incorporate rushing attack in one of the most commonly used mobile ad hoc network routing protocol namely Ad hoc on-demand multipath distance vector and provides rushing attack prevention method based on time threshold value and random route selection. Based on the time RREQ arrives a node takes a decision, if the RREQ packet arrives before threshold value, the RREQ packet consider as came from an attacker and discarded else RREQ packet received then randomly select RREQ to forward. In this study performance metrics like packet delivery ratio, end to end delay and throughput have been evaluated using Network simulation (NS-2.35). As a result of simulation shows newly proposed prevention mechanism improves network performance in all cases than the network under attacker. For example average packet delivery ratio enhanced from 54.37% to 97.69%, throughput increased from 20.84bps to 33.06bps and the average delay decreased from 1147.22ms to 908.04ms. We concluded that new proposed techniques show improvement in all evaluated performance metrics.