Machine Learning Techniques to Detect DDoS Attacks on VANET System: A Survey

Road traffic accidents and their sequences increase dramatically worldwide and thus raising a demand for solutions to providing safety and control of vehicles on road when driving. This is one of the top priorities for modern countries focusing on enhancing citizens' quality of life by developing an Intelligent Transport System (ITS). Vehicular Ad hoc NETworks (VANETs) are recognized to be effective in realizing such a concept. VANET is potential in improving road safety and in providing travelers comfort. However, such technology is still exposed to many vulnerabilities led to numerous of security threats that must be solved before VANET technology is practically and safely adopted. One of the main threats that affects the availability of VANET is Distributed Denial of Service (DDoS) attack. In this paper, we focus on studying the main attacks along with DDoS attack on VANET system as well as exploring potential solutions with a focus on machine learning based solutions to detect such attacks in this field.