Artificial Intelligence for Cybersecurity: Develop AI approaches to solve cybersecurity problems in your organization

This book has clearly and explicitly explain the role automation plays in contemporary cybersecurity practices particularly in an industrial setup.

As a GenAI practitioner exploring applications in cybersecurity, I found "Artificial Intelligence for Cybersecurity" to be an exceptionally well-crafted resource. It strikes an excellent balance between theoretical depth and practical implementation.Highlights:* Conceptual Clarity: The book begins with a strong conceptual grounding in AI/ML relevant to security, then transitions smoothly into the specifics of data engineering and its significance in cyber contexts. * Algorithm Deep Dive: Provides a robust overview of essential ML algorithms and their statistical basis – a valuable refresher for practitioners, specifically tailored to cybersecurity use cases. * Practical Python Code: The hands-on Python examples are genuinely useful for understanding how to implement the discussed techniques, covering areas like anomaly detection and threat intelligence analysis. * Addressing Real-World Challenges: Chapter 17's focus on learning in changing and adversarial environments is particularly salient, tackling the complexities of deploying AI in the dynamic landscape of cybersecurity. The inclusion of * Responsible AI principles (Chapter 18) also adds significant value for ethical deployment. This book is highly recommended for data scientists, AI/ML engineers, and cybersecurity professionals looking to bridge the gap between artificial intelligence and practical security applications. It provides both the 'why' and the 'how' effectively.

Artificial Intelligence for Cybersecurity covers a great deal of ground for Developers, Cybersecurity professionals, and AI Professionals operating at the intersection of AI and Cybersecurity.Part I of the book provides a good introductory overview of the technologies used in modern cybersecurity departments, including Big Data, and Data Analytics. (If you're coming from a heavy security background, you can skip ahead).Part II provided a great introduction into the basics of AI (If you are a developer with a year of experience in AI, you can skip this part).After getting all of the readers up to speed on both, Part III of the book then delves into practical examples, demonstrating how AI can assist in improving cybersecurity workflows for effectiveness, speed, and agility. The exercises provide instructions for MacOS, Ubuntu, and Windows. They leverage Python/Conda, using libraries such as Langchain, OpenAI, Tensorflow, Numpy, and others. Readers can delve into examples including Malware/Intrusion Detection; Behavior Analysis; Spam Detection; User Access Control; and Threat Intelligence. These practical examples, and hands-on exercises give the reader a strong feel for how AI might be applied to solve real cybersecurity problems.The last part of the book dives into common problems in implementing AI, including: Data Quality, Bias, How to Monitor AI Systems & Monitor Performance, AI Transparency, and Privacy.Overall, this book contains a well thought out curriculum to get people jumpstarted in Cybersecurity for AI, and a little hands-on experience with basic applications that will give them a feel for how problems can be tackled in the real world.

Packt has been coming out with some great books. This book has a lot of great information in it though I'm not sure where to place it or if the title is correct. There is good information on the background of AI and how it works, all of which is important to know as one contemplates security. I would have like to see a more deliberate focus on novel approaches to addressing AI security.The book is formatted well, clear references, and all the technical things you would expect. Not a disappointment, though for a seasoned IT programmer and cybersecurity professional, it might leave you wanting a little more from the authors.

This book is an outstanding blend of technical depth and practical utility. For cybersecurity professionals, it serves as both a reference manual for AI integration and a field guide for selecting and applying the right tools in real-world environments. Whether you're a SOC analyst, threat hunter, or security engineer, this book will sharpen your AI edge and future-proof your defensive strategies.Highly recommend it.

This book is poorly written. Lots of long, run-on sentences filled with excessive commas and AI buzzwords. It almost reads like AI-generated slop. Not recommended.