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Cybercrime and Cybersecurity Challenges in the Automotive Industry Utilizing Agent-Based Modeling (ABM)

Cybercrime and Cybersecurity Challenges in the Automotive Industry Utilizing Agent-Based Modeling (ABM)

Eugene Lewis, Darrell Norman Burrell, Calvin Nobles, Jennifer Ferreras-Perez, Kevin Richardson, Angel J. Jones, Laura Ann Jones
Copyright: © 2023 |Pages: 26
ISBN13: 9798369316344|ISBN13 Softcover: 9798369348604|EISBN13: 9798369316351
DOI: 10.4018/979-8-3693-1634-4.ch008
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MLA

Lewis, Eugene, et al. "Cybercrime and Cybersecurity Challenges in the Automotive Industry Utilizing Agent-Based Modeling (ABM)." Transformational Interventions for Business, Technology, and Healthcare, edited by Darrell Norman Burrell, IGI Global, 2023, pp. 134-159. https://doi.org/10.4018/979-8-3693-1634-4.ch008

APA

Lewis, E., Burrell, D. N., Nobles, C., Ferreras-Perez, J., Richardson, K., Jones, A. J., & Jones, L. A. (2023). Cybercrime and Cybersecurity Challenges in the Automotive Industry Utilizing Agent-Based Modeling (ABM). In D. Burrell (Ed.), Transformational Interventions for Business, Technology, and Healthcare (pp. 134-159). IGI Global. https://doi.org/10.4018/979-8-3693-1634-4.ch008

Chicago

Lewis, Eugene, et al. "Cybercrime and Cybersecurity Challenges in the Automotive Industry Utilizing Agent-Based Modeling (ABM)." In Transformational Interventions for Business, Technology, and Healthcare, edited by Darrell Norman Burrell, 134-159. Hershey, PA: IGI Global, 2023. https://doi.org/10.4018/979-8-3693-1634-4.ch008

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Abstract

Agent-based modeling (ABM) serves as a powerful and innovative tool to evaluate and address cybersecurity risks in the auto industry. With the increasing integration of advanced technologies in modern vehicles, the potential vulnerabilities and threats to cybersecurity have become a major concern. ABM allows cybersecurity experts to simulate complex interactions among autonomous agents representing various components of the automotive ecosystem, such as vehicles, manufacturers, suppliers, and hackers. ABM can effectively model real-world scenarios and assess how cyber threats propagate and spread throughout the system. It enables the identification of critical points of weakness and potential attack vectors, aiding in the development of proactive strategies to mitigate cybersecurity risks. Through iterative simulations and data-driven analysis, ABM empowers stakeholders in the auto industry to make informed decisions and implement robust security measures that safeguard against cyber-attacks, ensuring the safety and trustworthiness of connected and autonomous vehicles.

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