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Adversarial AI Threat Response and Secure Model Design : Practical Techniques for Detecting, Preventing, and Managing AI Vulnerabilities.
- Format:
- Book
- Author/Creator:
- Trajkovski, Goran.
- Series:
- Professional and Applied Computing Series
- Language:
- English
- Subjects (All):
- Artificial intelligence--Security measures.
- Artificial intelligence.
- Physical Description:
- 1 online resource (363 pages)
- Edition:
- 1st ed.
- Place of Publication:
- Berkeley, CA : Apress L. P., 2026.
- Summary:
- As artificial intelligence becomes embedded in everything from healthcare diagnostics to financial systems and autonomous vehicles, the stakes for AI security have never been higher. Adversarial AI Threat Response and Secure Model Design is your essential guide to understanding, defending against, and designing resilient machine learning systems.
- Contents:
- Chapter 1: The AI Security Threat Field
- Chapter 2: Understanding Adversarial Examples
- Chapter 3: Attacks Beyond Vision
- Chapter 4: Advanced Threat Techniques
- Chapter 5: Detecting the Invisible
- Chapter 6: Building Robust Models
- Chapter 7: Defensive Preprocessing Techniques
- Chapter 8: Ensemble and Layered Defense Systems
- Chapter 9: Quantifying Adversarial Risk
- Chapter 10: Responsibility, Liability, and Law
- Chapter 11: Ethical Challenges and Disclosure
- Chapter 12: Societal Impact and Deepfakes
- Chapter 13: Emerging Threats
- Chapter 14: Tools and Libraries for Attack and Defense
- Chapter 15: Case Studies in Real-World Adversarial AI
- Chapter 16: Guided Hands-on Projects.
- Notes:
- Description based on publisher supplied metadata and other sources.
- ISBN:
- 979-88-6882-308-4
- OCLC:
- 1587070074
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