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Adversarial AI Attacks, Mitigations, and Defense Strategies

You're reading from   Adversarial AI Attacks, Mitigations, and Defense Strategies A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps

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Product type Paperback
Published in Jul 2024
Publisher Packt
ISBN-13 9781835087985
Length 586 pages
Edition 1st Edition
Languages
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Author (1):
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John Sotiropoulos John Sotiropoulos
Author Profile Icon John Sotiropoulos
John Sotiropoulos
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Toc

Table of Contents (27) Chapters Close

Preface 1. Part 1: Introduction to Adversarial AI FREE CHAPTER
2. Chapter 1: Getting Started with AI 3. Chapter 2: Building Our Adversarial Playground 4. Chapter 3: Security and Adversarial AI 5. Part 2: Model Development Attacks
6. Chapter 4: Poisoning Attacks 7. Chapter 5: Model Tampering with Trojan Horses and Model Reprogramming 8. Chapter 6: Supply Chain Attacks and Adversarial AI 9. Part 3: Attacks on Deployed AI
10. Chapter 7: Evasion Attacks against Deployed AI 11. Chapter 8: Privacy Attacks – Stealing Models 12. Chapter 9: Privacy Attacks – Stealing Data 13. Chapter 10: Privacy-Preserving AI 14. Part 4: Generative AI and Adversarial Attacks
15. Chapter 11: Generative AI – A New Frontier 16. Chapter 12: Weaponizing GANs for Deepfakes and Adversarial Attacks 17. Chapter 13: LLM Foundations for Adversarial AI 18. Chapter 14: Adversarial Attacks with Prompts 19. Chapter 15: Poisoning Attacks and LLMs 20. Chapter 16: Advanced Generative AI Scenarios 21. Part 5: Secure-by-Design AI and MLSecOps
22. Chapter 17: Secure by Design and Trustworthy AI 23. Chapter 18: AI Security with MLSecOps 24. Chapter 19: Maturing AI Security 25. Index 26. Other Books You May Enjoy

Security and Adversarial AI

Now that we have our first end-to-end AI service, we will discuss how to secure it and demonstrate why traditional cybersecurity is inadequate against the new breed of adversarial AI attacks. We will perform our first adversarial attack on our image recognition service. We will define adversarial AI and discuss how it relates to conventional security problems.

More specifically, you will learn about fundamental security concepts, effective approaches to secure computer systems, and how to apply baseline security to our adversarial AI playground and how this relates to adversarial AI. This will help you do the following:

  • Understand fundamental security concepts such as the CIA triad, security frameworks such as NIST, threat modeling, security controls, DevSecOps, and MLOps, and how they all relate
  • Secure and harden your deployment host
  • Secure your environment from intruders, restrict access to the Service API, and protect against Denial...
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