Security Challenges in Autonomous Systems Design

TL;DR

This paper reviews security challenges in autonomous systems, highlighting issues in AI, data, and system interaction, and proposes research directions to enhance their security and trustworthiness.

Contribution

It provides a comprehensive overview of emerging security challenges in autonomous systems and suggests future research directions to address these issues.

Findings

Identifies key security challenges across multiple domains.

Discusses the state of the art in autonomous system security.

Proposes research directions for secure autonomous system development.

Abstract

Autonomous systems are emerging in many application domains. With the recent advancements in artificial intelligence and machine learning, sensor technology, perception algorithms and robotics, scenarios previously requiring strong human involvement can be handled by autonomous systems. With the independence from human control, cybersecurity of such systems becomes even more critical as no human intervention in case of undesired behavior is possible. In this context, this paper discusses emerging security challenges in autonomous systems design which arise in many domains such as autonomous incident response, risk assessment, data availability, systems interaction, trustworthiness, updatability, access control, as well as the reliability and explainability of machine learning methods. In all these areas, this paper thoroughly discusses the state of the art, identifies emerging security challenges and proposes research directions to address these challenges for developing secure autonomous systems.