Large Language Models in Cybersecurity: Threats, Exposure and Mitigation, edited by Andrei Kucharavy, provides an in-depth examination of how large language models (LLMs) intersect with cybersecurity.
Published by Springer in 2024, this book offers a detailed look at the challenges and solutions related to LLM security.
A great perk is that Springer published the book as ‘Open Access's, which means it is downloadable for everyone without a fee.
What is the Book About?
The book investigates the impact of LLMs on cybersecurity, discussing their applications, potential threats, and mitigation strategies. It addresses how LLMs can both pose and solve security issues, covering various scenarios where these models could be exploited or protected.
Table of Contents
The book begins with an introduction to large language models (LLMs) and their main application areas. It then examines the significant cybersecurity threats posed by LLMs, such as their potential use by cybercriminals and as new attack surfaces. Following this, it forecasts the development of LLM technologies and discusses regulatory measures to enhance cybersecurity. The book also presents strategies for the safe and secure development and deployment of LLMs. Finally, it speculates on secure LLM integration from first principles and summarizes the dual nature of LLMs in cybersecurity.
Readability and Completeness
The book is well-structured and accessible, making complex topics understandable without oversimplifying them. It balances technical detail with readability, providing a diligent and comprehensive coverage of LLM-related security issues. This is no surprise since the amount of contributors for this book is extensive: I counted 35 contributors and seven reviewers.
But this benefit comes with a (small) price. Sometime it’s not as convenient to read several chapters from different contributors, due to their writing style. Since all of them are researchers from renowned universities, it doesn’t matter very much, but it’s noticeable.
However, I would have loved to see more about references to industry standards like the ISO/IEC 42001 or the NIST AI Risk Management Framework (NIST AI RMF). the ISO/IEC 42001 isn’t mentioned at all and the NIST AI RMF only got a brief introductionary section.
Who Should Read It?
This book is essential for cybersecurity professionals, LLM developers, policymakers, and academic researchers. It offers valuable knowledge for anyone involved in the development, deployment, or regulation of LLMs within a cybersecurity program.
Résumé & Rating
"Large Language Models in Cybersecurity" is a great resource, offering thorough insights and practical guidance on managing the cybersecurity risks associated with LLMs. Its blend of technical depth and accessibility makes it a vital read for professionals and newcomers alike, providing a solid foundation for understanding and addressing the cybersecurity challenges posed by LLMs. On the downside, if you will, the amount of contributors and the different writing styles could make it more challenging to read.
Rating: 7,5/10