Robust Intrusion Detection Systems for In-Vehicle Networks in Autonomous Vehicles - A Machine Learning Perspective: Develops robust intrusion detection systems for in-vehicle networks in AVs, utilizing machine learning techniques
Published 20-06-2022
Keywords
- Intrusion Detection Systems,
- Autonomous Vehicles,
- In-Vehicle Networks
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
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Abstract
In recent years, the automotive industry has witnessed a rapid evolution towards autonomous vehicles (AVs), which heavily rely on in-vehicle networks for communication and operation. However, the increasing connectivity and complexity of these networks have exposed them to various cyber threats, including intrusion attempts. To ensure the safety and security of AVs, robust intrusion detection systems (IDS) are essential. This paper presents a comprehensive review of existing IDS for in-vehicle networks and proposes a novel approach based on machine learning techniques to enhance the robustness of IDS in AVs. We discuss the challenges and limitations of current IDS, and then delve into the application of machine learning algorithms for intrusion detection. Experimental results demonstrate the effectiveness of our proposed approach, highlighting its potential to significantly improve the security of in-vehicle networks in autonomous vehicles.
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References
- Tatineni, Sumanth. "Beyond Accuracy: Understanding Model Performance on SQuAD 2.0 Challenges." International Journal of Advanced Research in Engineering and Technology (IJARET) 10.1 (2019): 566-581.
- Vemoori, Vamsi. "Comparative Assessment of Technological Advancements in Autonomous Vehicles, Electric Vehicles, and Hybrid Vehicles vis-à-vis Manual Vehicles: A Multi-Criteria Analysis Considering Environmental Sustainability, Economic Feasibility, and Regulatory Frameworks." Journal of Artificial Intelligence Research 1.1 (2021): 66-98.
- Shaik, Mahammad, Srinivasan Venkataramanan, and Ashok Kumar Reddy Sadhu. "Fortifying the Expanding Internet of Things Landscape: A Zero Trust Network Architecture Approach for Enhanced Security and Mitigating Resource Constraints." Journal of Science & Technology 1.1 (2020): 170-192.
- Vemori, Vamsi. "Human-in-the-Loop Moral Decision-Making Frameworks for Situationally Aware Multi-Modal Autonomous Vehicle Networks: An Accessibility-Focused Approach." Journal of Computational Intelligence and Robotics 2.1 (2022): 54-87.