Part of the wider development and monitoring of smart environments for an intelligent cities approach is the building of an intelligent transportation system. Such a system involves the development of modern vehicles which significantly improve passenger safety and comfort, a trend that is expected to increase in the coming years. There are key factors relating to safety impacts and security vulnerabilities that may emerge during the increased deployment of automated vehicles and the security and privacy of connected and automated vehicle systems. They include ways of defining the security of malware-relevant system boundaries including electronic control units, silicon hardware, software, vehicle systems, infrastructure, network connectivity and more. In addition, vehicle industries are facing many problems with critical security and privacy issues, influenced by the smart environments for an intelligent cities approach. Such problems are related to hardware and software applications that allow the interfacing of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure networks (V2I). In this chapter, we present connected car methods relating to the attack, defence and detection of malware in vehicles. Critical issues are introduced regarding the sharing of safety information and the verification of the integrity of this information from V2V and V2I networks. In particular, we discuss the challenges and review state-of-the-art intra-inter-vehicle communication. Hackers can access this information in V2V/V2I networks and broadcast fake messages and malware to break the security system by using weak points in vehicles and networks. We present important security approaches that are used in vehicles which can fully protect the vehicle security architecture by detecting the attempts made and the methods used by hackers to tackle malware and security problems in vehicles. We present a comprehensive overview of current research on advanced intra-inter-vehicle communication networks and identify outstanding research questions that may be used to achieve high levels of vehicle security and privacy in intelligent cities in the future.
|Title of host publication||Malware Analysis Using Artificial Intelligence and Deep Learning|
|Editors||Mark Stamp, Mamoun Alazab, Andrii Shalaginov|
|Number of pages||23|
|Publication status||Published - 20 Dec 2020|