Cyber Security Attacks on Vehicle Ad-hoc Network

Abstract

Vehicle Ad hoc Network (VANET) technology arose from the mobile ad-hoc network (MANET). The first mention of the term was in 2003. VANET allows vehicles to communicate with other vehicles and other Intelligent Transport Systems (ITS) facilities in their location range. The widespread use of VANET necessitates attention to security issues, to ensure that VANET systems and applications are secure and protected from misbehavior attacks and abnormal use. VANET is a low-level trust environment, meaning that anyone can have a used vehicle in the VANET environment. For this, attackers can fake or manipulate the network that broadcasts messages among vehicles. Additionally, a stable and secure VANET environment would allow the integration of VANET security with smart cities. This thesis aims to conduct a literature review and identify the security requirements needed to achieve a secure VANET environment. It also aims to develop an application to identify a VANET cybersecurity attack, focusing on attacks that target other vehicles’ location and identity and the ability to detect previous attacks. The goal will beachieved using a proposed algorithm that checks parameters such as vehicle identity sequence of location and speed. The thesis starts by introducing VANET architecture, communication, and applications. Then it provides a thorough review of the high-impact papers from the VANET field that explain VANET’s wide-ranging categories of architecture, layers, and applications. The important security requirements are then defined based on the three-information security triangle, emphasizing the VANET environment. For this thesis, an application of misbehaving attacks on the positioning and identity of VANET vehicles has been developed. Then, the outputs of the application use to analyze the misbehaviors attacks. Besides, the extracted dataset was used to apply a machine learning classification to analyze the attacks. The thesis provides a thorough discussion of the development of the application, analysis, and results. Finally, the proposed algorithm that can detect the misbehavior attack on vehicle location positioning and identity is introduced. All of that is important for humans' road safety and life protection.