Open access
Jul 2026
Evaluation Framework for Cross-Layer Intrusion Detection Based on ML Approaches
This work proposed a modular weight-based framework that evaluates cross-layer Machine Learning (ML) IDS across multiple dimensions, namely, detection effectiveness and generalizability, data quality, and attack coverage and practical deployability, and applied this framework to the state-of-the-art cross-layer ML IDS identified through the PRISMA framework.
Dimitrios Tasiopoulos, A. Xenakis, A. Lekidis et al.
· Electronics · 0 citations