Examining Modern Data Security and Privacy Protocols in Autonomous Vehicles

A fully automated, self-driving car can perceive its environment, determine the optimal route, and drive
unaided by human intervention for the entire journey. Connected autonomous vehicles (CAVs) have the
potential to drastically reduce accidents, travel time, and the environmental impact of road travel. Such
technology includes the use of several sensors, various algorithms, interconnected network connections,
and multiple auxiliary systems. CAVs have been subjected to attacks by malicious users to gain/deny
control of one or more of its various systems. Data security and data privacy is one such area of CAVs that
has been targeted via different types of attacks. The scope of this study is to present a good background
knowledge of issues pertaining to different attacks in the context of data security and privacy, as well
present a detailed review and analysis of eight very recent studies on the broad topic of security and
privacy related attacks. Methodologies including Blockchain, Named Data Networking, Intrusion
Detection System, Cognitive Engine, Adversarial Objects, and others have been investigated in the
literature and problem- and context-specific models have been proposed by their respective authors.