A Framework for IOC-Driven Early Warning Threat Intelligence

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Vol 2 No 2 (2025): Kwaghe International Journal of Sciences and Technology
Page Numbers: 242-257
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Published: Jun 28, 2025
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Authors:
Adereti Rasak Raji1, Adenomon M. O2, Gilbert I. O. Aimufua3, Steven I. Bassey4
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Adereti Rasak Raji
Nasarawa State University Keffi, Nigeria
Adenomon M. O
Nasarawa State University Keffi, Nigeria
Gilbert I. O. Aimufua
Nasarawa State University Keffi, Nigeria
Steven I. Bassey
Nasarawa State University Keffi, Nigeria

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.

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How to Cite
Raji, A. R., O, A. M., Aimufua, G. I. O., & Bassey, S. I. (2025). A Framework for IOC-Driven Early Warning Threat Intelligence. Kwaghe International Journal of Sciences and Technology, 2(2), 242-257. https://doi.org/10.58578/kijst.v2i2.6458

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Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.

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