{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4INHJY2PCGTDD6AHMLQB2FDCID","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"0a0a99d465f321a136e8a8ad4fe81b92e2e7e0a5e8e2602535f0e522efd8928c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-06T04:47:52Z","title_canon_sha256":"026458d9ab186c53c3ba0610f2ad80f2910fa47fc945fcc3012d99ac6b26c20b"},"schema_version":"1.0","source":{"id":"2505.03179","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2505.03179","created_at":"2026-07-05T10:59:11Z"},{"alias_kind":"arxiv_version","alias_value":"2505.03179v1","created_at":"2026-07-05T10:59:11Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2505.03179","created_at":"2026-07-05T10:59:11Z"},{"alias_kind":"pith_short_12","alias_value":"4INHJY2PCGTD","created_at":"2026-07-05T10:59:11Z"},{"alias_kind":"pith_short_16","alias_value":"4INHJY2PCGTDD6AH","created_at":"2026-07-05T10:59:11Z"},{"alias_kind":"pith_short_8","alias_value":"4INHJY2P","created_at":"2026-07-05T10:59:11Z"}],"graph_snapshots":[{"event_id":"sha256:05e0835c2708a3bfd7c7703fa60991baec85984d1d74f2926acb272b3a1e1f46","target":"graph","created_at":"2026-07-05T10:59:11Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2505.03179/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"This study investigates whether large language models (LLMs) can function as intelligent collaborators to bridge expertise gaps in cybersecurity decision-making. We examine two representative tasks-phishing email detection and intrusion detection-that differ in data modality, cognitive complexity, and user familiarity. Through a controlled mixed-methods user study, n = 58 (phishing, n = 34; intrusion, n = 24), we find that human-AI collaboration improves task performance,reducing false positives in phishing detection and false negatives in intrusion detection. A learning effect is also observe","authors_text":"Cecile Paris, Mohan Baruwal Chhetri, Ronal Singh, Shahroz Tariq, Surya Nepal","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-06T04:47:52Z","title":"Bridging Expertise Gaps: The Role of LLMs in Human-AI Collaboration for Cybersecurity"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2505.03179","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:ab8b1c3f583ff693c3f25679577e1e14a476d06761a684bc96b67376d9fbf86f","target":"record","created_at":"2026-07-05T10:59:11Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"0a0a99d465f321a136e8a8ad4fe81b92e2e7e0a5e8e2602535f0e522efd8928c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-05-06T04:47:52Z","title_canon_sha256":"026458d9ab186c53c3ba0610f2ad80f2910fa47fc945fcc3012d99ac6b26c20b"},"schema_version":"1.0","source":{"id":"2505.03179","kind":"arxiv","version":1}},"canonical_sha256":"e21a74e34f11a631f80762e01d146240e40bbde301898853ab4253447cc43788","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e21a74e34f11a631f80762e01d146240e40bbde301898853ab4253447cc43788","first_computed_at":"2026-07-05T10:59:11.572468Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:59:11.572468Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"d7vwWgyw+aA8gxnviKZ/ubVKCt6I+VdQOojnDmHwZYuwZsi0EayP7EwQ7hSgvJuNVkEWnBUUfWp15j4kvSZEDA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:59:11.573041Z","signed_message":"canonical_sha256_bytes"},"source_id":"2505.03179","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ab8b1c3f583ff693c3f25679577e1e14a476d06761a684bc96b67376d9fbf86f","sha256:05e0835c2708a3bfd7c7703fa60991baec85984d1d74f2926acb272b3a1e1f46"],"state_sha256":"efe1d5765c8d33b0d7f6c3ab7388892be46a50d7490d2ec8972f90c5ed1645ab"}