Anomaly Detection in IEC-61850 GOOSE Networks: Evaluating Unsupervised and Temporal Learning for Real-Time Intrusion Detection
arXiv 2604.14233•78210cc8c9950f7a7e23025221146bef2842c767e59a61b358c951b3b10c2e4e
Android securityBloom filterGOOSEGRUIEC-61850LLM agentsOWASP API Securityagentic systemsbackend vulnerabilitiescloud sovereigntycontrol planecross-environment generalizationexcessive data exposureface reidentificationhomomorphic encryptionindustrial control systemsmutual TLSpost-quantum cryptographyprivacy-preserving biometricsreal-time intrusion detectionreverse engineeringtemporal modelsunsupervised learningusabilityzero-day disclosure (responsible disclosure reported to vendor)
Paper metadata
- arXiv ID
- 2604.14233
- Version
- Not specified by this published record
- Category
- Computer Science — Cryptography and Security (cs.CR)
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Evidence and limitations
- Source ID
- arxiv_cs_cr
- Record identifier
- 78210cc8c9950f7a7e23025221146bef2842c767e59a61b358c951b3b10c2e4e
- Enrichment time
- 2026-04-17T07:23:33Z
- AI-assisted enrichment
- Yes
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