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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 FREE CHAPTER
2. Chapter 1: Big Data in Cybersecurity 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

Ethical considerations

Automation in cybersecurity introduces a plethora of ethical considerations that necessitate thorough examination. First and foremost, automated cybersecurity systems often rely on vast amounts of data to detect and respond to threats effectively. However, collecting, processing, and storing this data raises significant privacy concerns. Ethical practices dictate that individuals should be aware of the data being collected about them and give explicit consent for its use in cybersecurity measures. Moreover, ensuring that automated systems anonymize or pseudonymize data wherever possible helps protect individual privacy rights.

Next, algorithms powering automated cybersecurity tools may inherit biases in the training data. This can lead to discriminatory outcomes, such as unfairly targeting certain demographics or disproportionately flagging specific groups as potential threats. Ethical considerations demand ongoing scrutiny of these algorithms to identify...

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