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AI Native LLM Security. A comprehensive guide to leveraging OWASP Top 10 for LLM applications and beyond Vaibhav Malik, Ken Huang, Adam Dawson

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AI Native LLM Security. A comprehensive guide to leveraging OWASP Top 10 for LLM applications and beyond Vaibhav Malik, Ken Huang, Adam Dawson - okladka książki

AI Native LLM Security. A comprehensive guide to leveraging OWASP Top 10 for LLM applications and beyond Vaibhav Malik, Ken Huang, Adam Dawson - okladka książki

Autorzy:
Vaibhav Malik, Ken Huang, Adam Dawson
Serie wydawnicze:
Hands-on
Ocena:
Adversarial AI attacks present a unique set of security challenges, exploiting the very foundation of how AI learns. This book explores these threats in depth, equipping cybersecurity professionals with the tools needed to secure generative AI and LLM applications. Rather than skimming the surface of emerging risks, it focuses on practical strategies, industry standards, and recent research to build a robust defense framework.
Structured around actionable insights, the chapters introduce a secure-by-design methodology, integrating threat modeling and MLSecOps practices to fortify AI systems. You’ll discover how to leverage established taxonomies from OWASP, NIST, and MITRE to identify and mitigate vulnerabilities. Through real-world examples, the book highlights best practices for incorporating security controls into AI development life cycles, covering key areas like CI/CD, MLOps, and open-access LLMs.
Built on the expertise of its co-authors—pioneers in the OWASP Top 10 for LLM applications—this guide also addresses the ethical implications of AI security, contributing to the broader conversation on Trustworthy AI. By the end of this book, you’ll be able to develop, deploy, and secure AI technologies with confidence and clarity.

O autorze książki

Ken Huang is a renowned AI expert, serving as co-chair of AI Safety Working Groups at Cloud Security Alliance and the AI STR Working Group at World Digital Technology Academy under the UN Framework. As CEO of DistributedApps, he provides specialized GenAI consulting.
A key contributor to OWASP's Top 10 Risks for LLM Applications and NIST's Generative AI Working Group, Huang has authored influential books including Beyond AI (Springer, 2023), Generative AI Security (Springer, 2024), and Agentic AI: Theories and Practice (Springer, 2025)
He's a global speaker at prestigious events such as Davos WEF, ACM, IEEE, and RSAC. Huang is also a member of the OpenAI Forum and project leader for the OWASP AI Vulnerability Scoring System project.

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