Work

Explainable ML-Based Intrusion Detection for E-Government Cyber Defence

Year: 2026

Type: article

Abstract: This repository contains the source code, experimental notebooks, datasets/results, and supplementary materials associated with the research study: "Explainable Machine Learning-Based Intrusion Detection for e-Government Cyber Defence" The study investigates the use of explainable and trustworthy machine learning techniques for network intrusion detection, with emphasis on detection performance, probability calibration, and model interpretability.

Source: Zenodo (CERN European Organization for Nuclear Research)

DOI: 10.5281/zenodo.22148785

Author: Md Ashraful, Islam

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7204539053

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