Secure Over-the-Air Software Updates for Autonomous Vehicle Operating Systems
Keywords:
Connected vehicles, Electronic Control Units (ECU), Over-the-Air (OTA)Abstract
The key dilemma in OTA technology is how to update vehicle operating systems normally, without compromising public safety or losing vehicle trustworthiness. The most important concerns include, how to keep messages confidential, and how to balance the need for different security issues in the OTA system. The severity of these concerns regularly depends on a number of factors like the number of applications in the car, privacy laws, data ownership, and legal responsibilities. A common approach to develop the OTA system is to use asymmetric cryptography to sign software packages, and then through encrypting the same, protect their data integrity and confidentiality. This approach is very reliable, especially when using large, long cryptographic keys to sign and encrypt the data, but the many years of encryption overhead can be unacceptable for connected vehicle systems. To assist Support Variability, the multi-level system should have the necessary level of session confidentiality and integrity protection
The automotive industry is facing significant challenges as connected and autonomous vehicle technology accelerates. This shift is driven by an exponential rise in the number of electronic, intelligent embedded systems in cars, combined with the need for regular maintenance and updates for these systems. Ensuring the security of Over-The-Air (OTA) updates and software management in connected and autonomous vehicles is a complex issue that is rapidly moving into the scope of system and hardware developers. The objective of this paper is to propose a secure OTA software update protocol that is in line with the increasing importance of cybersecurity in smart vehicle design. In this paper, we present the key elements of the secure software update, essential to the development of secure connected and autonomous vehicle systems.
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References
Perumalsamy, Jegatheeswari, Bhargav Kumar Konidena, and Bhavani Krothapalli. "AI-Driven Risk Modeling in Life Insurance: Advanced Techniques for Mortality and Longevity Prediction." Journal of Artificial Intelligence Research and Applications 3.2 (2023): 392-422.
Karamthulla, Musarath Jahan, et al. "From Theory to Practice: Implementing AI Technologies in Project Management." International Journal for Multidisciplinary Research 6.2 (2024): 1-11.
Jeyaraman, J., Krishnamoorthy, G., Konidena, B. K., & Sistla, S. M. K. (2024). Machine Learning for Demand Forecasting in Manufacturing. International Journal for Multidisciplinary Research, 6(1), 1-115.
Karamthulla, Musarath Jahan, et al. "Navigating the Future: AI-Driven Project Management in the Digital Era." International Journal for Multidisciplinary Research 6.2 (2024): 1-11.
Karamthulla, M. J., Prakash, S., Tadimarri, A., & Tomar, M. (2024). Efficiency Unleashed: Harnessing AI for Agile Project Management. International Journal For Multidisciplinary Research, 6(2), 1-13.
Jeyaraman, Jawaharbabu, Jesu Narkarunai Arasu Malaiyappan, and Sai Mani Krishna Sistla. "Advancements in Reinforcement Learning Algorithms for Autonomous Systems." International Journal of Innovative Science and Research Technology (IJISRT) 9.3 (2024): 1941-1946.
Jangoan, Suhas, Gowrisankar Krishnamoorthy, and Jesu Narkarunai Arasu Malaiyappan. "Predictive Maintenance using Machine Learning in Industrial IoT." International Journal of Innovative Science and Research Technology (IJISRT) 9.3 (2024): 1909-1915.
Jangoan, Suhas, et al. "Demystifying Explainable AI: Understanding, Transparency, and Trust." International Journal For Multidisciplinary Research 6.2 (2024): 1-13.
Krishnamoorthy, Gowrisankar, et al. "Enhancing Worker Safety in Manufacturing with IoT and ML." International Journal For Multidisciplinary Research 6.1 (2024): 1-11.
Perumalsamy, Jegatheeswari, Muthukrishnan Muthusubramanian, and Lavanya Shanmugam. "Machine Learning Applications in Actuarial Product Development: Enhancing Pricing and Risk Assessment." Journal of Science & Technology 4.4 (2023): 34-65.
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