Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS_拉斯维加斯赌城

Today our paper “Agree to Disagree: Exploring Consensus of XAI Methods for ML-based NIDS” was presented at the 1st Workshop on Network Security Operations (NecSecOr). This paper examines the effectiveness and consensus of various explainable AI (XAI) methods in enhancing the interpretability of machine learning-based Network Intrusion Detection Systems (ML-NIDS), finding that while some methods align closely, others diverge, underscoring the need for careful selection to build trust in real-world cybersecurity applications.