Published Paper Details:

Vehicular Adhoc networks (VANETs) are the most promising research area. Implementation of VANETs needs to address issues on security, privacy and speed. Security in VANET works is very important. To address these issues, understanding that the attack is happening is very important. Our previous paper includes a comprehensive survey on security attacks in VANETs and the impact of attacks on the network. This paper discusses how efficiently Machine Learning algorithms help identify the attack. Machine Learning algorithms are widely used to make such predictions because of their well-accepted accuracy. This paper discusses DDoS, PortScan and DoS-Hulk attack classification using different trained models to see which algorithm is more effective and why. Models are developed using MATLAB. With the help of results, an attempt has been made to explain the reason for misclassification and why certain Machine Learning algorithms have greater classification accuracy.