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AI Security and Privacy

In: Understanding AI in Cybersecurity and Secure AI

Author

Listed:
  • Dilli Prasad Sharma

    (University of Toronto)

  • Arash Habibi Lashkari

    (York University)

  • Mahdi Daghmehchi Firoozjaei

    (MacEwan University)

  • Samaneh Mahdavifar

    (McGill University)

  • Pulei Xiong

    (National Research Council of Canada)

Abstract

This chapter provides an in-depth exploration of security and privacy concerns in Artificial Intelligence (AI), specifically focusing on the vulnerabilities and threats that arise from integrating AI systems. It begins with a discussion of AI’s security challenges, followed by a detailed examination of AI security and privacy attacks. This chapter also presents a comprehensive framework for analyzing adversarial attacks, including AI attack surface, attacker goals, attacker’s capabilities, and attack strategies. This framework enables a deeper understanding of attack types and their implications for AI security and privacy, providing critical insights into mitigating these risks in AI-driven systems.

Suggested Citation

  • Dilli Prasad Sharma & Arash Habibi Lashkari & Mahdi Daghmehchi Firoozjaei & Samaneh Mahdavifar & Pulei Xiong, 2025. "AI Security and Privacy," Progress in IS, in: Understanding AI in Cybersecurity and Secure AI, chapter 0, pages 137-158, Springer.
    • Handle: RePEc:spr:prochp:978-3-031-91524-6_8
    DOI: 10.1007/978-3-031-91524-6_8
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