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

Vehicular Ad hoc NETworks (VANET) are networks that allows communication between vehicles using their own connection infrastructure. There are several advantages and applications in using this technology; one of most significant is road safety. As in most other networks, it is very important to guarantee the transport and the security of information. The security in VANET is a big challenge because there are different types of attacks that endanger communications. This paper proposes an adaptive neuro-fuzzy inference system (ANFIS) applied to obtain a prediction model of security index in VANET. The research process starts with the network simulation to obtain the database that 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.