Adversarial Machine Learning
Mechanisms, Vulnerabilities, and Strategies for Trustworthy AI
$130.26
- Hardcover
400 pages
- Release Date
24 February 2026
Summary
Enables readers to understand the full lifecycle of adversarial machine learning (AML) and how AI models can be compromised
Adversarial Machine Learning is a definitive guide to one of the most urgent challenges in artificial intelligence today: how to secure machine learning systems against adversarial threats.
This book explores the full lifecycle of adversarial machine learning (AML), providing a structured, real-world understanding of how AI model…
Book Details
| ISBN-13: | 9781394402038 |
|---|---|
| ISBN-10: | 1394402031 |
| Author: | Jason Edwards |
| Publisher: | John Wiley & Sons Inc |
| Imprint: | John Wiley & Sons Inc |
| Format: | Hardcover |
| Number of Pages: | 400 |
| Release Date: | 24 February 2026 |
| Weight: | 0g |
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About The Author
Jason Edwards
Jason Edwards, DM, CISSP, is an accomplished cybersecurity leader with extensive experience in the technology, finance, insurance, and energy sectors. Holding a Doctorate in Management, Information Systems, and Technology, Jason specializes in guiding large public and private companies through complex cybersecurity challenges. His career includes leadership roles across the military, insurance, finance, energy, and technology industries. He is a husband, father, former military cyber officer, adjunct professor, avid reader, dog dad, and popular on LinkedIn.
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