Securing AI Systems: A Guide to Known Attacks and Impacts

TL;DR

This paper offers a comprehensive overview of AI-specific security threats, detailing eleven attack types and their impacts, to help stakeholders recognize risks and improve defenses in AI systems.

Contribution

It systematically categorizes AI-specific attacks and links them to security impacts, providing a foundational guide for security awareness and mitigation strategies.

Findings

Identified eleven major AI attack types

Mapped attack techniques to security impacts

Provided guidance for defense strategies

Abstract

Embedded into information systems, artificial intelligence (AI) faces security threats that exploit AI-specific vulnerabilities. This paper provides an accessible overview of adversarial attacks unique to predictive and generative AI systems. We identify eleven major attack types and explicitly link attack techniques to their impacts -- including information leakage, system compromise, and resource exhaustion -- mapped to the confidentiality, integrity, and availability (CIA) security triad. We aim to equip researchers, developers, security practitioners, and policymakers, even those without specialized AI security expertise, with foundational knowledge to recognize AI-specific risks and implement effective defenses, thereby enhancing the overall security posture of AI systems.