CyTReX: Explainable AI-Based Cybersecurity Threat Reasoning Framework for DER Networks
Distributed Energy Resource (DER) environments rely on network communication protocols to coordinate control commands, measurements, and device states across edge assets and cloud systems. Edge anomaly detection systems (ADS) monitor this traffic to identify deviations from normal communication behavior, flagging suspicious flows for further investigation. When the ADS flags abnormal network traffic, a single attack label is often insufficient for operational response: the label reports the detector's selected class but does not expose alternative threat interpretations that may warrant investigation. This paper presents Cybersecurity Threat Reasoning with Explainable Artificial Intellige...
| Authors | Damilola Popoola, Souradeep Bhattacharya, Manimaran Govindarasu |
|---|---|
| Primary category | cs.CR |
| Published | 3 October 2026 |
| Last updated at source | 3 October 2026 |
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