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Three Challenges to Secure AI Systems in the Context of AI Regulations

Ronan Hamon, H. Junklewitz, Josep Soler Garrido, Ignacio Sánchez

2024IEEE Access26 citationsDOIOpen Access PDF

Abstract

This article examines the interplay between artificial intelligence (AI) and cybersecurity in light of future regulatory requirements on the security of AI systems, specifically focusing on the robustness of high-risk AI systems against cyberattacks in the context of the European Union’s AI Act. The paper identifies and analyses three challenges to achieve compliance of AI systems with the cybersecurity requirement: accounting for the diversity and the complexity of AI technologies, assessing AI-specific risks, and developing secure-by-design AI systems. The contribution of the article consists in providing an overview of AI cybersecurity practices and identifying gaps in current approaches to security conformity assessment for AI systems. Our analysis highlights the unique vulnerabilities present in AI systems and the absence of established cybersecurity practices tailored to these systems, and emphasises the need for continuous alignment between legal requirements and technological capabilities, acknowledging the necessity for further research and development to address the challenges. It concludes that comprehensive cybersecurity practices must evolve to accommodate the unique aspects of AI, with a collaborative effort from various sectors to ensure effective implementation and standardisation.

Topics & Concepts

Computer scienceContext (archaeology)Computer securityPaleontologyBiologyAdversarial Robustness in Machine LearningAdvanced Malware Detection TechniquesEthics and Social Impacts of AI