What type of study is this?

This is a Experimental Study study.

September 12, 2025

Explainable AI for Cyber Threat Intelligence and Risk Assessment

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Authors

EOEhimah Obuse EEEdima David Etim IEIboro Akpan Essien

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Overview

This research develops an explainable AI framework that enhances risk assessment in cybersecurity, highlighting the importance of transparency and interpretability.

Key Points

The explainable AI framework significantly improves detection of advanced persistent threats, phishing, and zero-day exploits.
Experimental evaluations show high precision and recall in AI models while providing interpretable outputs that reduce decision latency.
Integrating machine learning with SHAP and LIME methodologies helps security analysts understand AI-generated insights confidently.
The research emphasizes the need for transparency in AI applications, fostering accountability and enhancing human-machine collaboration in security operations.

Cite This Study

Obuse et al. (2020) studied this question.

synapsesocial.com/papers/68d4768331b076d99fa6f027 https://doi.org/10.54660/.jfmr.2020.1.2.15-30

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September 12, 2025

Explainable AI for Cyber Threat Intelligence and Risk Assessment

View Full Paper

Ask AI

Bookmark

Authors

EOEhimah Obuse EEEdima David Etim IEIboro Akpan Essien

Discussion

Member takes

Overview

This research develops an explainable AI framework that enhances risk assessment in cybersecurity, highlighting the importance of transparency and interpretability.

Key Points

The explainable AI framework significantly improves detection of advanced persistent threats, phishing, and zero-day exploits.
Experimental evaluations show high precision and recall in AI models while providing interpretable outputs that reduce decision latency.
Integrating machine learning with SHAP and LIME methodologies helps security analysts understand AI-generated insights confidently.
The research emphasizes the need for transparency in AI applications, fostering accountability and enhancing human-machine collaboration in security operations.

Cite This Study

Obuse et al. (2020) studied this question.

synapsesocial.com/papers/68d4768331b076d99fa6f027 https://doi.org/10.54660/.jfmr.2020.1.2.15-30

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