{"paper":{"title":"HySecTwin: A Knowledge-Driven Digital Twin Framework Augmented with Hybrid Reasoning for Cyber-Physical Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"HySecTwin combines semantic modeling with hybrid deterministic and fuzzy reasoning in digital twins to deliver faster, explainable threat detection for cyber-physical systems.","cross_cats":[],"primary_cat":"cs.CR","authors_text":"Ahmad Moshin, David Holmes, Helge Yanicke, Iqbal Sarker, Leslie Sikos, Surya Nepal","submitted_at":"2026-05-12T07:41:31Z","abstract_excerpt":"Existing Digital Twin (DT) approaches often lack semantic reasoning capabilities for effective cybersecurity modelling in Cyber-Physical Systems (CPS). This paper presents HySecTwin, a knowledge-driven digital twin architecture that places automated reasoning at the core of real-time threat detection. HySecTwin incorporates semantic modelling to transform heterogeneous CPS telemetry, device attributes, and operational relationships into machine-interpretable representations, combined with an embedded reasoning engine operating over contextualized system states. Unlike opaque detection methods,"},"claims":{"count":4,"items":[{"kind":"strongest_claim","text":"Experimental evaluation using a representative CPS testbed and MITRE ATT&CK campaign-inspired attack scenarios demonstrates sub-millisecond twin synchronization latency and up to 21.5% faster threat detection compared with deterministic reasoning alone.","source":"verdict.strongest_claim","status":"machine_extracted","claim_id":"C1","attestation":"unclaimed"},{"kind":"weakest_assumption","text":"The representative CPS testbed and MITRE ATT&CK-inspired scenarios sufficiently capture the complexity, heterogeneity, and real-time dynamics of actual mission-critical cyber-physical systems.","source":"verdict.weakest_assumption","status":"machine_extracted","claim_id":"C2","attestation":"unclaimed"},{"kind":"one_line_summary","text":"HySecTwin integrates semantic modeling with hybrid deterministic and fuzzy reasoning in digital twins to achieve faster, more interpretable threat detection in CPS with sub-millisecond latency.","source":"verdict.one_line_summary","status":"machine_extracted","claim_id":"C3","attestation":"unclaimed"},{"kind":"headline","text":"HySecTwin combines semantic modeling with hybrid deterministic and fuzzy reasoning in digital twins to deliver faster, explainable threat detection for cyber-physical systems.","source":"verdict.pith_extraction.headline","status":"machine_extracted","claim_id":"C4","attestation":"unclaimed"}],"snapshot_sha256":"7a0b68b400b7ade5cf53994632fb8cf7b12deede5824123d4713b04ca015af16"},"source":{"id":"2605.11682","kind":"arxiv","version":2},"verdict":{"id":"6bdc833b-c3b0-4a2a-84be-6320e1ece9fc","model_set":{"reader":"grok-4.3"},"created_at":"2026-05-13T00:57:24.542560Z","strongest_claim":"Experimental evaluation using a representative CPS testbed and MITRE ATT&CK campaign-inspired attack scenarios demonstrates sub-millisecond twin synchronization latency and up to 21.5% faster threat detection compared with deterministic reasoning alone.","one_line_summary":"HySecTwin integrates semantic modeling with hybrid deterministic and fuzzy reasoning in digital twins to achieve faster, more interpretable threat detection in CPS with sub-millisecond latency.","pipeline_version":"pith-pipeline@v0.9.0","weakest_assumption":"The representative CPS testbed and MITRE ATT&CK-inspired scenarios sufficiently capture the complexity, heterogeneity, and real-time dynamics of actual mission-critical cyber-physical systems.","pith_extraction_headline":"HySecTwin combines semantic modeling with hybrid deterministic and fuzzy reasoning in digital twins to deliver faster, explainable threat detection for cyber-physical systems."},"integrity":{"clean":false,"summary":{"advisory":1,"critical":1,"by_detector":{"doi_compliance":{"total":2,"advisory":1,"critical":1,"informational":0}},"informational":0},"endpoint":"/pith/2605.11682/integrity.json","findings":[{"note":"DOI in the printed bibliography is fragmented by whitespace or line breaks. A longer candidate (10.1016/j.cose.2022.102578) was visible in the surrounding text but could not be confirmed against doi.org as printed.","detector":"doi_compliance","severity":"advisory","ref_index":38,"audited_at":"2026-05-19T08:13:23.629093Z","detected_doi":"10.1016/j.cose.2022.102578","finding_type":"recoverable_identifier","verdict_class":"incontrovertible","detected_arxiv_id":null},{"note":"Identifier '10.1145/3597507' is syntactically valid but the DOI registry (doi.org) returned 404, and Crossref / OpenAlex / internal corpus also have no record. The cited work could not be located through any authoritative source.","detector":"doi_compliance","severity":"critical","ref_index":51,"audited_at":"2026-05-19T08:13:23.629093Z","detected_doi":"10.1145/3597507","finding_type":"unresolvable_identifier","verdict_class":"cross_source","detected_arxiv_id":null}],"available":true,"detectors_run":[{"name":"doi_title_agreement","ran_at":"2026-05-21T00:01:32.289154Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"doi_compliance","ran_at":"2026-05-20T14:07:05.904847Z","status":"completed","version":"1.0.0","findings_count":2},{"name":"claim_evidence","ran_at":"2026-05-20T03:42:00.520264Z","status":"completed","version":"1.0.0","findings_count":0},{"name":"ai_meta_artifact","ran_at":"2026-05-19T11:40:03.296616Z","status":"completed","version":"1.0.0","findings_count":0}],"snapshot_sha256":"4938327102174ea8d9915c037593355d4311deb2ec09ee370166c867b736d493"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}