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January 1, 2026International Journal of Information and Computer Security

Cross-year cyber-attack detection and temporal generalisation: an explainable machine learning approach

Archana R. Laddhad Gurveen Vaseer

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Key Points

This research aims to enhance the detection of cyber-attacks using machine learning techniques that generalize across different time periods.
Utilized explainable machine learning algorithms to analyze cyber-attack patterns
Examined data from multiple years to improve detection accuracy
Focused on temporal generalization methods for broader applicability
Achieved significant improvement in detection rates over traditional methods
Demonstrated strong predictive performance across different time frames
Provided insights into temporal patterns of cyber-attacks, enhancing response strategies

Implication

Explainable machine learning detects cyber-attacks across years, suggesting improved security measures.

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Cite This Study

Laddhad et al. (2026) studied this question.

synapsesocial.com/papers/6a17dcdf3fad632b0f9d997c https://doi.org/10.1504/ijics.2026.10078770

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