LEVERAGING CYBER THREAT INTELLIGENCE MINING FOR ENHANCED PROACTIVE CYBERSECURITY: A COMPREHENSIVE REVIEW AND FUTURE DIRECTIONS
Abstract
In the contemporary digital age, the sophistication and frequency of cyberattacks necessitate a paradigm shift from reactive defense to proactive cybersecurity measures. Cyber Threat Intelligence (CTI) has emerged as a cornerstone of this proactive strategy, enabling organizations to anticipate, detect, and respond to threats more effectively. This article provides a comprehensive survey of cyber threat intelligence mining, exploring its fundamental concepts, diverse sources, and the advanced techniques employed for extracting actionable insights from vast, often unstructured, data. We delve into various approaches, from the identification of Indicators of Compromise (IoCs) and Tactics, Techniques, and Procedures (TTPs) to the complex challenge of threat attribution. Furthermore, we highlight the significant challenges inherent in CTI mining, including data volume, veracity, semantic understanding, and the crucial aspect of translating intelligence into actionable defense. Finally, we propose new perspectives and promising research directions to advance the field of proactive cybersecurity through more effective CTI mining.
Keywords
References
Similar Articles
- Dr. Nisha Verma, Vinay Rajan, OPTIMIZING CRYPTOGRAPHIC HASH FUNCTION PERFORMANCE THROUGH AN EXTENDED SECURE HASH ALGORITHM (2080-BIT VARIANT) , International Journal of Cyber Threat Intelligence and Secure Networking: Vol. 2 No. 06 (2025): Volume 02 Issue 06
You may also start an advanced similarity search for this article.