Abstract
There is a critical gap in research relating to the human factors of cybersecurity: within the context of AV operation, what impact do certain cybersecurity breaches, or classes of breaches, have on the operator’s task focus and decision-making processes? [1]. The national highway transportation safety administration (NHTSA) has identified several areas of “substantial barriers to deployment of highly-automated vehicles” including issues of trust and ethical implications, societal acceptance, data sharing, vehicle-to-vehicle, and vehicle-to-infrastructure. The security of the human factor in cybersecurity falls into the wider social issues surrounding human trust and automated vehicles. Necessary research may be categorized into psychological cyberattacks, which seek to model and understand the human factors contributing to attacks. Specific subcategories of these, that is, cyberterrorism and, more relevant to the present study, human factors in automobile surveillance, with a focus on the vehicle operator, who is the only person who can reasonably neutralize an attack.
References
[1] V. Linkov, P. Zámečník, D. Havlíčková, and C. W. Pai, "Human Factors in the Cybersecurity of Autonomous Vehicles: Trends in Current Research," 2019. ncbi.nlm.nih.gov
[2] P. Xiong, S. Buffett, S. Iqbal, P. Lamontagne et al., "Towards a Robust and Trustworthy Machine Learning System Development: An Engineering Perspective," 2021. [PDF]
[3] S. A. Abdel Hakeem, H. H. Hussein, and H. W. Kim, "Security Requirements and Challenges of 6G Technologies and Applications," 2022. ncbi.nlm.nih.gov
Tatineni, Sumanth. "Blockchain and Data Science Integration for Secure and Transparent Data Sharing." International Journal of Advanced Research in Engineering and Technology (IJARET) 10.3 (2019): 470-480.
Leeladhar Gudala, et al. “Leveraging Artificial Intelligence for Enhanced Threat Detection, Response, and Anomaly Identification in Resource-Constrained IoT Networks”. Distributed Learning and Broad Applications in Scientific Research, vol. 5, July 2019, pp. 23-54, https://dlabi.org/index.php/journal/article/view/4.
Vemori, Vamsi. "Towards Safe and Equitable Autonomous Mobility: A Multi-Layered Framework Integrating Advanced Safety Protocols, Data-Informed Road Infrastructure, and Explainable AI for Transparent Decision-Making in Self-Driving Vehicles." Human-Computer Interaction Perspectives 2.2 (2022): 10-41.
[7] M. Chowdhury, M. Islam, and Z. Khan, "Security of Connected and Automated Vehicles," 2020. [PDF]
[8] D. Haileselassie Hagos and D. B. Rawat, "Recent Advances in Artificial Intelligence and Tactical Autonomy: Current Status, Challenges, and Perspectives," 2022. ncbi.nlm.nih.gov
[9] A. Dinesh Kumar, K. Naga Renu Chebrolu, V. R, and S. KP, "A Brief Survey on Autonomous Vehicle Possible Attacks, Exploits and Vulnerabilities," 2018. [PDF]
[10] A. Sarker, H. Shen, M. Rahman, M. Chowdhury et al., "A Review of Sensing and Communication, Human Factors, and Controller Aspects for Information-Aware Connected and Automated Vehicles," 2019. [PDF]
[11] Y. Guan, H. Liao, Z. Li, G. Zhang et al., "World Models for Autonomous Driving: An Initial Survey," 2024. [PDF]
[12] X. Li, Y. Wang, J. Guo, R. Liu et al., "Radial velocity map of solar wind transients in the field of view of STEREO/HI1 on 3 and 4 April 2010," 2021. [PDF]
[13] A. K. Ligo, A. Kott, and I. Linkov, "Autonomous Cyber Defense Introduces Risk: Can We Manage the Risk?," 2022. [PDF]
[14] M. Hamad and S. Steinhorst, "Security Challenges in Autonomous Systems Design," 2023. [PDF]
[15] M. Grobler, R. Gaire, and S. Nepal, "User, Usage and Usability: Redefining Human Centric Cyber Security," 2021. ncbi.nlm.nih.gov
[16] M. Hijji and G. Alam, "Cybersecurity Awareness and Training (CAT) Framework for Remote Working Employees," 2022. ncbi.nlm.nih.gov
[17] Y. Shao, S. Weerdenburg, J. Seifert, H. Paul Urbach et al., "Wavelength-multiplexed Multi-mode EUV Reflection Ptychography based on Automatic-Differentiation," 2023. [PDF]
[18] V. V. Dixit, S. Chand, and D. J. Nair, "Autonomous Vehicles: Disengagements, Accidents and Reaction Times," 2016. ncbi.nlm.nih.gov
[19] M. Chu, K. Zong, X. Shu, J. Gong et al., "Work with AI and Work for AI: Autonomous Vehicle Safety Drivers' Lived Experiences," 2023. [PDF]
[20] A. Pollini, T. C. Callari, A. Tedeschi, D. Ruscio et al., "Leveraging human factors in cybersecurity: an integrated methodological approach," 2021. ncbi.nlm.nih.gov