Securing Autonomous Systems: A Challenge for AI Safety

Abstract

Autonomous systems, powered by Artificial Intelligence (AI), have become an integral part of many sectors, including transportation, healthcare, defense, and manufacturing. These systems, which range from self-driving vehicles to robotic process automation, promise significant benefits in terms of efficiency, safety, and scalability. However, as autonomous systems become increasingly prevalent, securing these systems against vulnerabilities becomes critical to ensuring their safe deployment and operation. The integration of AI into autonomous systems introduces new challenges in terms of robustness, reliability, and safety. Adversarial attacks, system malfunctions, and cybersecurity threats present serious risks to the operation of these systems. This paper examines the security challenges associated with autonomous systems and explores strategies for enhancing their safety. It also highlights the implications of AI-driven decision-making in critical environments and the need for robust security mechanisms to mitigate potential risks. By reviewing current research, identifying existing gaps, and proposing future research directions, this paper provides a comprehensive overview of securing autonomous systems in the context of AI safety.