Cyber Threat Intelligence : Challenges and Opportunities

Abstract

The ever increasing number of cyber attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost realtime. In practice, timely dealing with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions, this in essence defines cyber threat intelligence notion. However, such an intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyse, and interpret cyber attack evidences. In this introductory chapter we first discuss the notion of cyber threat intelligence and its main challenges and opportunities, and then briefly introduce the chapters of the book which either address the identified challenges or present opportunistic solutions to provide threat intelligence.

5 Pages

References in corpus (6)

• Leveraging Machine Learning Techniques for Windows Ransomware Network Traffic Detection
• Machine Learning Aided Static Malware Analysis: A Survey and Tutorial
• Leveraging Support Vector Machine for Opcode Density Based Detection of Crypto-Ransomware
• Emerging from The Cloud: A Bibliometric Analysis of Cloud Forensics Studies
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Cited by in corpus (4)

• The New Frontier of Cybersecurity: Emerging Threats and Innovations
• Digital Forensics vs. Anti-Digital Forensics: Techniques, Limitations and Recommendations
• Distributed Threat Intelligence at the Edge Devices: A Large Language Model-Driven Approach
• Generating Cyber Threat Intelligence to Discover Potential Security Threats Using Classification and Topic Modeling