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Artificial Intelligence for Cybersecurity

You're reading from   Artificial Intelligence for Cybersecurity Develop AI approaches to solve cybersecurity problems in your organization

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781805124962
Length 358 pages
Edition 1st Edition
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Authors (4):
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Bojan Kolosnjaji Bojan Kolosnjaji
Author Profile Icon Bojan Kolosnjaji
Bojan Kolosnjaji
Apostolis Zarras Apostolis Zarras
Author Profile Icon Apostolis Zarras
Apostolis Zarras
Huang Xiao Huang Xiao
Author Profile Icon Huang Xiao
Huang Xiao
Peng Xu Peng Xu
Author Profile Icon Peng Xu
Peng Xu
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Toc

Table of Contents (27) Chapters Close

Preface 1. Part 1: Data-Driven Cybersecurity and AI
2. Chapter 1: Big Data in Cybersecurity FREE CHAPTER 3. Chapter 2: Automation in Cybersecurity 4. Chapter 3: Cybersecurity Data Analytics 5. Part 2: AI and Where It Fits In
6. Chapter 4: AI, Machine Learning, and Statistics - A Taxonomy 7. Chapter 5: AI Problems and Methods 8. Chapter 6: Workflow, Tools, and Libraries in AI Projects 9. Part 3: Applications of AI in Cybersecurity
10. Chapter 7: Malware and Network Intrusion Detection and Analysis 11. Chapter 8: User and Entity Behavior Analysis 12. Chapter 9: Fraud, Spam, and Phishing Detection 13. Chapter 10: User Authentication and Access Control 14. Chapter 11: Threat Intelligence 15. Chapter 12: Anomaly Detection in Industrial Control Systems 16. Chapter 13: Large Language Models and Cybersecurity 17. Part 4: Common Problems When Applying AI in Cybersecurity
18. Chapter 14: Data Quality and its Usage in the AI and LLM Era 19. Chapter 15: Correlation, Causation, Bias, and Variance 20. Chapter 16: Evaluation, Monitoring, and Feedback Loop 21. Chapter 17: Learning in a Changing and Adversarial Environment 22. Chapter 18: Privacy, Accountability, Explainability, and Trust – Responsible AI 23. Part 5: Final Remarks and Takeaways
24. Chapter 19: Summary 25. Index 26. Other Books You May Enjoy

Privacy, Accountability, Explainability, and Trust – Responsible AI

As the deployment of artificial intelligence (AI) technologies becomes increasingly pervasive across various sectors, addressing the associated privacy, accountability, explainability, and trust issues is paramount, particularly in the realm of cybersecurity. These aspects are collectively referred to as the pillars of Responsible AI, a framework that advocates for the ethical development, deployment, and management of AI systems.

This chapter aims to provide a comprehensive overview of the challenges, significance, and ways to tackle the issues surrounding AI security and safety, offering insights into both theoretical perspectives and practical guidelines. We will elucidate why it is crucial to maintain a strict governance framework around AI, and how neglecting these responsibilities can lead not only to increased risks but also to a wide range of unintended, potentially grave, consequences.

The importance...

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