Skip to Main content Skip to Navigation
Conference papers

Autonomous Vehicle Security: Literature Review of Real Attack Experiments

Abstract : With recent advances in technology to bring about smarter cities, significant efforts are put forth to enhance living standards through efficient infrastructure and services. Smart mobility is a core aspect of the Smart City concept, looking for the design of smart solutions to the challenging urban traffic issues faced by modern cities. It is envisioned that vehicle automation will come to change our lives and society soon. Autonomous vehicles have been around for years now, driving around streets to test their ability to navigate real-world driving environments. In the long term, they are expected to improve road safety and increase citizens mobility, providing a suitable mode of transport for people who cannot drive. Although the technology is not yet mature, it has aroused the interest of both academia and industry to inherent security challenges that must be addressed before large-scale adoption. There has been a host of research efforts on the security of autonomous vehicles in terms of vulnerabilities, attacks and potential defenses. In this paper, we propose a novel taxonomy of attack surfaces in autonomous vehicles. Based on our taxonomy, we review a selection of relevant and recent research on real attack experiments carried out on many components and automated driving systems. We also perform threat modeling and risk assessment to support security aware design of autonomous vehicles.
Document type :
Conference papers
Complete list of metadata
Contributor : Mawloud Omar Connect in order to contact the contributor
Submitted on : Tuesday, December 1, 2020 - 7:09:12 PM
Last modification on : Tuesday, November 16, 2021 - 4:29:32 AM


  • HAL Id : hal-03034640, version 1


Siham Bouchelaghem, Abdelmadjid Bouabdallah, Mawloud Omar. Autonomous Vehicle Security: Literature Review of Real Attack Experiments. The 15th International Conference on Risks and Security of Internet and Systems, 2020, Paris, France. ⟨hal-03034640⟩



Record views