Multi-Layer Perceptron Based Fuzzy Logic Technique for Detection of Attacks in VANETS

Vehicles are imparting messages with other vehicles in ad hoc network, which is referred as VANET communication. Due to the emerging of new technologies as part of industry 4.0 the VANET as frequently used in communication applications. But in this cyber attacks are increased in the VANETS communications. Scholars have proposed different solutions and algorithms to find the attacks. Here we have proposed a method that uses artificial intelligence. The proposed method is the combination of Neural Network based Multilayer Perceptron (MLP) trained Fuzzy Logic System procedure to spot unusual behavior of automobiles in the ad hoc network. To validate the results time of detection, positive rate, and ratio of detection is used. The outcome will giv the better performance existing methods.