Implications of Cyber-Physical Adversarial Attacks on Autonomous Systems

Amit Kumar Bairwa; Rahul Yadav; Deepak Dasaratha Rao; Kanchan Naidu; Yogeesha H C; Sorabh Sharma

doi:10.52756/ijerr.2024.v46.021

Authors

Amit Kumar Bairwa Department of Artificial Intelligence and Machine Learning, Manipal University Jaipur, India https://orcid.org/0000-0003-1830-0661
Rahul Yadav Lead Application Architect, Information Technology, University of Rajasthan, Jaipur, India https://orcid.org/0009-0001-8052-3340
Deepak Dasaratha Rao Independent Researcher, Indian Institute of Technology, Patna, India https://orcid.org/0000-0001-5959-3136
Kanchan Naidu Department of Management Technology, Shri Ramdeobaba College of Engineering and Management, Nagpur, Maharashtra, India https://orcid.org/0000-0001-5362-2135
Yogeesha H C Department of Mechanical Engineering, Nagarjuna College of Engineering and Technology, Bangalore, India https://orcid.org/0000-0003-1113-9123
Sorabh Sharma Centre of Research Impact and Outcome, Chitkara University, Rajpura, Punjab, India https://orcid.org/0009-0000-1805-0418

DOI:

https://doi.org/10.52756/ijerr.2024.v46.021

Keywords:

Adversarial Attacks, Autonomous Systems, Comparative Analysis, Cyber-Physical, Real-World Relevance

Abstract

This study examines hostile cyber-physical assaults on autonomous systems and proposes a novel approach. The recommended strategy integrates many domains, evaluates data quantitatively, and emphasizes real-world applications. A detailed comparison of six conventional approaches is underway. Four graphics depict the comparative study and how the recommended strategy would handle cyber-physical hostile assault challenges. The recommended solution utilizes multidisciplinary research, prioritizes quantitative reviews, and demonstrates its practical application and adaptability to various security challenges, thereby establishing a robust framework. Our analysis highlights the key advantages of the recommended technique by comparing six well-known methodologies. Clear illustrations support these findings, demonstrating the potential of the approach. The grid shows its strong presence across important criteria, and the radar image shows its success in data-driven analysis, freedom, and real-world application. The scatter plot illustrates that the technique is flexible and quantitative review-friendly, supporting its approach. Results reveal that the recommended technique is powerful and comprehensive. This helps analyze and mitigate cyber-physical hostile assaults on autonomous systems. Visualizations make it simple and fast to compare the recommended method to regular methods and discover its substantial advantages. This research will make autonomous systems safer and more resistant to new threats, ensuring their safety and consistency.

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Implications of Cyber-Physical Adversarial Attacks on Autonomous Systems

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