Evaluating ML-based Intrusion Detection Systems: The Illusion of Model Efficacy

arXiv:2609.02469 · cs.CR · Submitted 2026-09-02 · Read on arXiv

cs.CR

Submitted: 2026-09-02

Updated: 2026-09-02

Terminology

Generalization — 67× in this paper · explained in 13 episodes
Feature Selection — 30× in this paper · explained in 4 episodes
Accuracy — 22× in this paper · explained in 1 episode
Machine Learning — 18× in this paper
Robustness — 8× in this paper · explained in 5 episodes
Benchmark — 7× in this paper · explained in 2 episodes
Interpretability — 7× in this paper · explained in 15 episodes
Network Intrusion Detection Systems — 5× in this paper
Domain Shift — 4× in this paper · explained in 4 episodes
Core — 3× in this paper · explained in 2 episodes
Explainability — 3× in this paper · explained in 3 episodes
Adversarial Robustness — 2× in this paper · explained in 3 episodes
Transferability — 2× in this paper · explained in 4 episodes
Adaptability — 1× in this paper · explained in 1 episode
Aggregation — 1× in this paper · explained in 1 episode
Algorithmic Improvements — 1× in this paper · explained in 1 episode
Concept Drift — 1× in this paper · explained in 4 episodes
Feature Extraction — 1× in this paper · explained in 2 episodes
Fine-Tuning — 1× in this paper · explained in 5 episodes
Generalizability — 1× in this paper · explained in 6 episodes
Meta-learning — 1× in this paper · explained in 2 episodes
Model-Agnostic — 1× in this paper · explained in 2 episodes
Multimodal Dataset — 1× in this paper · explained in 2 episodes
Random Forest — 1× in this paper
SHAP values — 1× in this paper · explained in 2 episodes

Terminology

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