AI Security: Cyber Threats and Threat-Informed Defense
Kamal Singh, Rohit Saxena, Brijesh Kumar · 2024
Artificial intelligence has emerged as a revolution-ary technology offering substantial advances over traditional information and communication systems. However, the increasing prevalence of AI introduces new vulnerabilities, making AI-driven systems more susceptible to cybercriminal activities and security threats aimed at disrupting their operations. This study comprehensively examines the cybersecurity challenges and threats associated with AI applications, emphasizing the core principles of information security. Confidentiality, Integrity, and Availability. The study categorizes AI-related threats into two key areas: first, threats targeting critical AI components such as data, models, and algorithms, and second, the malicious exploitation of AI to conduct sophisticated, large-scale cyberattacks. This analysis contributes to a threat-informed defense by examining risk assessment methodologies to address these challenges, under-scoring the need for robust security frameworks. Furthermore, it leverages the Adversarial Threat Landscape for Artificial Intelligence Systems (ATLAS) guidelines, offering future research directions to enhance AI security, and providing practical recom-mendations for securing AI across diverse deployment scenarios.