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Adversarial AI Attacks, Mitigations, and Defense Strategies
Adversarial AI Attacks, Mitigations, and Defense Strategies

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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Profile Icon John Sotiropoulos
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$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (13 Ratings)
Paperback Jul 2024 602 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
Arrow left icon
Profile Icon John Sotiropoulos
Arrow right icon
$12.99 per month
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9 (13 Ratings)
Paperback Jul 2024 602 pages 1st Edition
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m
eBook
$39.99
Paperback
$49.99
Subscription
Free Trial
Renews at $12.99p/m

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Key benefits

  • Understand the unique security challenges presented by predictive and generative AI
  • Explore common adversarial attack strategies as well as emerging threats such as prompt injection
  • Mitigate the risks of attack on your AI system with threat modeling and secure-by-design methods
  • Purchase of the print or Kindle book includes a free PDF eBook

Description

Adversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips you with the skills to secure AI technologies, moving beyond research hype or business-as-usual activities. Learn how to defend AI and LLM systems against manipulation and intrusion through adversarial attacks such as poisoning, trojan horses, and model extraction, leveraging DevSecOps, MLOps, and other methods to secure systems. This strategy-based book is a comprehensive guide to AI security, combining structured frameworks with practical examples to help you identify and counter adversarial attacks. Part 1 introduces the foundations of AI and adversarial attacks. Parts 2, 3, and 4 cover key attack types, showing how each is performed and how to defend against them. Part 5 presents secure-by-design AI strategies, including threat modeling, MLSecOps, and guidance aligned with OWASP and NIST. The book concludes with a blueprint for maturing enterprise AI security based on NIST pillars, addressing ethics and safety under Trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI systems against the threat of adversarial attacks effectively.

Who is this book for?

This book tackles AI security from both angles - offense and defence. AI developers and engineers will learn how to create secure systems, while cybersecurity professionals, such as security architects, analysts, engineers, ethical hackers, penetration testers, and incident responders will discover methods to combat threats to AI and mitigate the risks posed by attackers. The book also provides a secure-by-design approach for leaders to build AI with security in mind. To get the most out of this book, you’ll need a basic understanding of security, ML concepts, and Python.

What you will learn

  • Set up a playground to explore how adversarial attacks work
  • Discover how AI models can be poisoned and what you can do to prevent this
  • Learn about the use of trojan horses to tamper with and reprogram models
  • Understand supply chain risks
  • Examine how your models or data can be stolen in privacy attacks
  • See how GANs are weaponized for Deepfake creation and cyberattacks
  • Explore emerging LLM-specific attacks, such as prompt injection
  • Leverage DevSecOps, MLOps and MLSecOps to secure your AI system

Product Details

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Publication date, Length, Edition, Language, ISBN-13
Publication date : Jul 26, 2024
Length: 602 pages
Edition : 1st
Language : English
ISBN-13 : 9781835087985
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Product Details

Publication date : Jul 26, 2024
Length: 602 pages
Edition : 1st
Language : English
ISBN-13 : 9781835087985
Category :
Languages :
Tools :

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Rating distribution
Full star icon Full star icon Full star icon Full star icon Half star icon 4.9
(13 Ratings)
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Dwayne Natwick Sep 02, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I recently received a copy of @Packt Publishing’s Adversarial AI Attacks, Mitigations, and Defense Strategies from @John Sotiropoulos. This book outlines that various types of AI attacks along with the anatomy and design of these attacks. The author provides information on the architecture and setup that can be used for detailed analysis, mitigation, and defense of these attacks. There is also a complete section on generative AI and how it is used for a new level of attacks. Throughout this book, the author has done a great job of developing understanding and knowledge for the reader about these attacks, how they are created, and how you can protect your environment against them. This book is highly recommended for anyone that is looking for a level of understanding about how to architect, monitor, and defend against AI attacks.
Amazon Verified review Amazon
T J Coup Aug 01, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
A highly necessary book in the field, this comprehensive guide to AI security offers a structured understanding of key issues, complete with hands-on examples. A must-read for all IT professionals this summer.
Amazon Verified review Amazon
Brandon Lachterman Sep 06, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I really enjoyed this book, and it will be a fixture on my virtual shelf for reference. In a subject just getting more traction, this book gets down to brass tax and covers the subjects any reader is looking for, while leaving out the extra fluff. Very technical, but clear to understand. Highly recommend.
Amazon Verified review Amazon
Brian Oct 18, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
There is limited material on this topic and I am about 4 chapters in and I have enjoyed the walkthrough on setting up a lab as the background... will update as I continue through the book.
Amazon Verified review Amazon
Steve Wilson Aug 12, 2024
Full star icon Full star icon Full star icon Full star icon Full star icon 5
The media could not be loaded. "Adversarial AI Attacks, Mitigations, and Defense Strategies" by John Sotiropoulos is a must-have resource for cybersecurity professionals navigating the complexities of AI security.This book is an incredibly in-depth guide that tackles the intricate details of defending AI systems from adversarial attacks. It’s highly technical, making it an excellent choice for those with a solid background in cybersecurity, machine learning, and system administration. Sotiropoulos doesn’t shy away from the details, providing comprehensive code examples, system admin settings, and scripts that are invaluable for practical implementation.One of the standout aspects of this book is its coverage of both predictive and generative AI. This dual focus ensures that readers are well-equipped to handle security challenges across different AI applications. Whether you're dealing with machine learning models in a predictive context or exploring the relatively newer field of generative AI, this book has you covered.If you’re looking for a technical, hands-on approach to securing AI systems, this book is an essential addition to your library.
Amazon Verified review Amazon
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