Design and modeling an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of a security index in VANET

Vehicular Ad hoc NETworks (VANET) allow communications between vehicles using their own connection infrastructure. There are several advantages and applications in using this technology and one of most significant is road safety. As in most other networks, it is not only important to guarantee the transport but also the security of information. Security in VANET is a big challenge because there are different types of attacks that endanger communications of moving vehicles. This paper proposes an applied Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain a prediction model of security index in VANET. The research process starts with network simulations to obtain a database of occurrences of attacks. Then, this latter is prepared and analyzed statistically. Finally, using MATLAB toolbox, we show the proposed model of security level that allows estimating the network vulnerability in the event of an attack.