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This chapter presents a general framework for AI security and privacy. It begins with examining security threats and defenses across key phases of the AI system development life cycle, including data collection, preprocessing, model training, inference, and system integration. The chapter discusses NIST’s AI Risk Management Framework (AI RMF), focusing on risk identification, system trustworthiness, and the lifecycle dimensions of AI systems. It also outlines core frameworks, including Google’s Secure AI Framework, and relevant security and privacy standards, such as ISO/IEC AI security standards, EU AI Act, and OECD AI principles.

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General Framework for AI Security and Privacy

  • 章节

  • 发表日期：

    2025年

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  • Dilli Prasad Sharma,
  • Arash Habibi Lashkari,
  • Mahdi Daghmehchi Firoozjaei,
  • Samaneh Mahdavifar,
  • Pulei Xiong

摘要

This chapter presents a general framework for AI security and privacy. It begins with examining security threats and defenses across key phases of the AI system development life cycle, including data collection, preprocessing, model training, inference, and system integration. The chapter discusses NIST’s AI Risk Management Framework (AI RMF), focusing on risk identification, system trustworthiness, and the lifecycle dimensions of AI systems. It also outlines core frameworks, including Google’s Secure AI Framework, and relevant security and privacy standards, such as ISO/IEC AI security standards, EU AI Act, and OECD AI principles.