Systematic Review on the Recent Trends of Cybersecurity in Automobile Industry

Abstract

The increasing integration of technology in automobiles has raised industry concerns about cyber-security. This paper provides an overview of the most recent developments in automobile cyber-security practices, pointing out the most important areas of cyber security that need more research in the context of self-driving cars and the automobile industry. Considering the different communities of cybersecurity mapped out by previous researchers, we explored each of these communities with respect to automobiles. The community of cybersecurity is subjected to intrusion detection, cryptography, sensor networks, information hiding, intrusion detection, biometrics, authentication, usable security, and access control. From the systematic review done, we found out the bulk of security research in the automobile industry is geared towards intrusion detection. The use of chaos-based picture encryption, visual cryptography, biometric fingerprinting, keystroke dynamics, background subtraction, gait identification, provable security, provable data possession, block ciphers, differential power analysis, hardware trojans, physical unclonable functions, etc., although used in the industry, has yet to be explored with respect to the security of vehicles, their networks, and the automobile industry. The results show that some of the different communities of cybersecurity towards automobiles are still in their infancy with opportunities for novel work.