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All Journal Kwaghe International Journal of Sciences and Technology
Adenomon M. O
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Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Environmental Science Law, Crime, Criminology & Criminal Justice Social Sciences

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A Framework for IOC-Driven Early Warning Threat Intelligence Adereti Rasak Raji; Adenomon M. O; Gilbert I. O. Aimufua; Steven I. Bassey
Kwaghe International Journal of Sciences and Technology Vol 2 No 2 (2025): Kwaghe International Journal of Sciences and Technology
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/kijst.v2i2.6458

Abstract

The increasing sophistication of cyber threats necessitates a strategic transition from reactive defenses to proactive threat mitigation. Although Indicators of Compromise (IoCs) serve as essential forensic artifacts in post-incident analysis, their potential for early threat detection remains underutilized due to issues such as data overload, insufficient contextualization, and rapid obsolescence. This study proposes the IoC-Driven Early Warning (IDEW) framework to address these limitations. The IDEW framework introduces a structured, multi-stage approach that includes multi-source data aggregation, advanced IoC validation and scoring, real-time correlation and pattern detection, and the generation of context-rich early warnings. Through systematic processing, the framework enhances the accuracy and timeliness of threat detection, allowing organizations to identify and respond to emerging cyber threats at earlier stages. Grounded in current literature and operational insights, this framework offers a conceptual foundation for integrating IoCs more effectively into proactive cybersecurity strategies.
Co-Authors Adereti Rasak Raji Gilbert I. O. Aimufua Steven I. Bassey