Prevention of Malicious Nodes Using Genetic Algorithm in Vehicular Ad Hoc Network

Abstract

VANET a thrilling function via mobile ad-hoc network (MANETs). VANET is a dominant invention which can supply practical vehicle to roadside infrastructure (V2I) communiqué and vehicle to vehicle (V2V). VANETs are a natural configure scheme wherein node are automobile and WIFI technology are used to shape networks. VANETs is a accredited construct intelligent transportation system (ITS) which emphasis on road protection, visitor well being and traffic effectiveness. In existing work, the supply node use extra data well identified as pseudo reply packet (PRREP). Supply node saves all details regarding entire arriving package in look-up chart chosen as RREP_T. The chart save series of PRREP set in ascending way via using POP and PUSHES processes. If there is any kind of deviation in chart order will be measured to PRREP series got via malicious node and will be rejected via source. Shortest series digits gives peak priority and it is measured via series digits. Nodes that have irregular series digits are measured as malicious node and supply transmit message via network. But depending on sequence number is not useful concept for the detection of malicious node in the network. In the proposed work, we overcome this problem via usage of genetic algorithm to recover performance in network. If the node has less fitness value than the threshold value than it is considered as a misbehaviour node. By this technique we can improve the performance of network by removing malicious nodes. We used NS2 in the simulation to provide the implementation work to provide the efficiency in the network.