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All Journal African Multidisciplinary Journal of Sciences and Artificial Intelligence Kwaghe International Journal of Sciences and Technology
Adereti Rasak Raji
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Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Environmental Science Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Social Sciences

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Implementing and Evaluating an IoC-Driven Early Warning System for Enhanced Cybersecurity Resilience Adereti Rasak Raji; Adenomon M. O.; Gilbert I. O.; Aimufua Steven I. Bassey
African Multidisciplinary Journal of Sciences and Artificial Intelligence Vol 2 No 2 (2025): African Multidisciplinary Journal of Sciences and Artificial Intelligence
Publisher : Darul Yasin Al Sys

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58578/amjsai.v2i2.6805

Abstract

In the contemporary digital landscape, organizations are increasingly confronted by sophisticated cyber threats that render traditional reactive security measures inadequate, particularly in the face of advanced persistent threats (APTs) and rapidly evolving attack vectors. This paper proposes the design, implementation, and evaluation of an Indicator of Compromise (IoC)-driven Early Warning System (EWS) to proactively bolster cybersecurity resilience. Grounded in the principles of Cyber Threat Intelligence (CTI) and Design Science Research (DSR), the proposed framework termed the Intelligent Detection and Early Warning (IDEW) System integrates multiple threat intelligence feeds, employs advanced analytics for real-time threat detection, and delivers actionable insights to support timely incident response. The study explores the theoretical foundations of CTI and DSR, outlines key architectural considerations for the IDEW System, and presents a conceptual case study illustrating its application in identifying and mitigating emerging threats, including the 'Salt Typhoon' APT campaign. Additionally, the paper addresses challenges in operationalizing CTI, such as data integration, contextual relevance, and alert fatigue, and underscores the importance of human expertise, robust data governance, and iterative refinement for effective system deployment. This research contributes to the evolving discourse on proactive cybersecurity strategies, offering a structured, intelligence-driven approach to building adaptive and resilient defense mechanisms in a dynamic threat environment.
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 Adenomon M. O Adenomon M. O. Aimufua Steven I. Bassey Gilbert I. O. Gilbert I. O. Aimufua Steven I. Bassey