Reliability auditing of explanations for machine-learning-based intrusion detection systems
Machine-learning-based intrusion detection systems can learn nonlinear and interaction-based traffic patterns that are difficult to capture using static rules, but their predictions remain difficult to interpret reliably in analyst-facing cybersecurity workflows. This paper proposes a unified quantitative framework for...