Explainable Machine Learning Framework for Distributed Denial-of-Service (DDoS) Attack Detection using Comparative Evaluation and SHAP Analysis

Today's article comes from the journal of Aviation Electronics, Information Technology, Telecommunications, Electricals, and Controls (AVITEC). The authors are Riziq et al., from Universitas Pendidikan, in Indonesia. In this paper, they focus on the explainability side of attack detection. They benchmark a set of supervised learning algorithms against each other, apply SHAP analysis to the best-performing model, and then introduce a new metric they call the Feature Stability Score (FSS).

DOI: 10.28989/avitec.v8i1.3594