{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:UZSRIGAUVVGOWJ5RHNOJGNEZDR","short_pith_number":"pith:UZSRIGAU","canonical_record":{"source":{"id":"2402.19366","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-02-29T17:13:44Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"576c239ec60e07d2339c7f9c9fee8d105813259f6572293e8292fb0c90226b73","abstract_canon_sha256":"eebafa2c74766ca436652d41364d9ed0443996d871f6abc32a044d0af89b81b7"},"schema_version":"1.0"},"canonical_sha256":"a665141814ad4ceb27b13b5c9334991c6dd9a34aad8bb8b91d3b09937274420b","source":{"kind":"arxiv","id":"2402.19366","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19366","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19366v3","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19366","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_12","alias_value":"UZSRIGAUVVGO","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_16","alias_value":"UZSRIGAUVVGOWJ5R","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_8","alias_value":"UZSRIGAU","created_at":"2026-07-05T10:07:39Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:UZSRIGAUVVGOWJ5RHNOJGNEZDR","target":"record","payload":{"canonical_record":{"source":{"id":"2402.19366","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-02-29T17:13:44Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"576c239ec60e07d2339c7f9c9fee8d105813259f6572293e8292fb0c90226b73","abstract_canon_sha256":"eebafa2c74766ca436652d41364d9ed0443996d871f6abc32a044d0af89b81b7"},"schema_version":"1.0"},"canonical_sha256":"a665141814ad4ceb27b13b5c9334991c6dd9a34aad8bb8b91d3b09937274420b","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:07:39.660210Z","signature_b64":"ZUBbXR/zRt01lcnKfhkpnewZPvZW1Wmfu+vd8t82iXOK3xClHbLSQjP8Qk4WQaLGNrxz6lG41RQbxwV1+fZLAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a665141814ad4ceb27b13b5c9334991c6dd9a34aad8bb8b91d3b09937274420b","last_reissued_at":"2026-07-05T10:07:39.659723Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:07:39.659723Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2402.19366","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:07:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"uDpezC7yFrNG9N2ULyQvOtDbCN22Qkg+ENVReXR5zJYBA6BL+O7tuQwFEIQwafoHLZxWjiskoJgAmhaIUYQMAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:16:39.504258Z"},"content_sha256":"9641aa004f5936ec04d732c92c17f6e213a419cec68e838a9e59c1a8110f5b22","schema_version":"1.0","event_id":"sha256:9641aa004f5936ec04d732c92c17f6e213a419cec68e838a9e59c1a8110f5b22"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:UZSRIGAUVVGOWJ5RHNOJGNEZDR","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Exploring the Potential of Large Language Models for Improving Digital Forensic Investigation Efficiency","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CR","authors_text":"Akila Wickramasekara, Frank Breitinger, Mark Scanlon","submitted_at":"2024-02-29T17:13:44Z","abstract_excerpt":"The ever-increasing workload of digital forensic labs raises concerns about law enforcement's ability to conduct both cyber-related and non-cyber-related investigations promptly. Consequently, this article explores the potential and usefulness of integrating Large Language Models (LLMs) into digital forensic investigations to address challenges such as bias, explainability, censorship, resource-intensive infrastructure, and ethical and legal considerations. A comprehensive literature review is carried out, encompassing existing digital forensic models, tools, LLMs, deep learning techniques, an"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19366","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2402.19366/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:07:39Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"twFwgXNbGYBUi8HlZj9k9ieTr1QX45A+sNj15XkwFaA5CGZiK/eDUQXbVQn2DxnjwDhg6Nk6iUu2UcEzQP1bCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T09:16:39.504763Z"},"content_sha256":"5dc176d36df55f345e4e6d6b1d7a414f0b64ade580bf825ab5f7af6da8896ea7","schema_version":"1.0","event_id":"sha256:5dc176d36df55f345e4e6d6b1d7a414f0b64ade580bf825ab5f7af6da8896ea7"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/bundle.json","state_url":"https://pith.science/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-09T09:16:39Z","links":{"resolver":"https://pith.science/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR","bundle":"https://pith.science/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/bundle.json","state":"https://pith.science/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UZSRIGAUVVGOWJ5RHNOJGNEZDR/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:UZSRIGAUVVGOWJ5RHNOJGNEZDR","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":"eebafa2c74766ca436652d41364d9ed0443996d871f6abc32a044d0af89b81b7","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-02-29T17:13:44Z","title_canon_sha256":"576c239ec60e07d2339c7f9c9fee8d105813259f6572293e8292fb0c90226b73"},"schema_version":"1.0","source":{"id":"2402.19366","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2402.19366","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"arxiv_version","alias_value":"2402.19366v3","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2402.19366","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_12","alias_value":"UZSRIGAUVVGO","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_16","alias_value":"UZSRIGAUVVGOWJ5R","created_at":"2026-07-05T10:07:39Z"},{"alias_kind":"pith_short_8","alias_value":"UZSRIGAU","created_at":"2026-07-05T10:07:39Z"}],"graph_snapshots":[{"event_id":"sha256:5dc176d36df55f345e4e6d6b1d7a414f0b64ade580bf825ab5f7af6da8896ea7","target":"graph","created_at":"2026-07-05T10:07:39Z","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/2402.19366/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The ever-increasing workload of digital forensic labs raises concerns about law enforcement's ability to conduct both cyber-related and non-cyber-related investigations promptly. Consequently, this article explores the potential and usefulness of integrating Large Language Models (LLMs) into digital forensic investigations to address challenges such as bias, explainability, censorship, resource-intensive infrastructure, and ethical and legal considerations. A comprehensive literature review is carried out, encompassing existing digital forensic models, tools, LLMs, deep learning techniques, an","authors_text":"Akila Wickramasekara, Frank Breitinger, Mark Scanlon","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-02-29T17:13:44Z","title":"Exploring the Potential of Large Language Models for Improving Digital Forensic Investigation Efficiency"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2402.19366","kind":"arxiv","version":3},"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":"sha256:9641aa004f5936ec04d732c92c17f6e213a419cec68e838a9e59c1a8110f5b22","target":"record","created_at":"2026-07-05T10:07:39Z","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":"eebafa2c74766ca436652d41364d9ed0443996d871f6abc32a044d0af89b81b7","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-02-29T17:13:44Z","title_canon_sha256":"576c239ec60e07d2339c7f9c9fee8d105813259f6572293e8292fb0c90226b73"},"schema_version":"1.0","source":{"id":"2402.19366","kind":"arxiv","version":3}},"canonical_sha256":"a665141814ad4ceb27b13b5c9334991c6dd9a34aad8bb8b91d3b09937274420b","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a665141814ad4ceb27b13b5c9334991c6dd9a34aad8bb8b91d3b09937274420b","first_computed_at":"2026-07-05T10:07:39.659723Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:07:39.659723Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ZUBbXR/zRt01lcnKfhkpnewZPvZW1Wmfu+vd8t82iXOK3xClHbLSQjP8Qk4WQaLGNrxz6lG41RQbxwV1+fZLAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T10:07:39.660210Z","signed_message":"canonical_sha256_bytes"},"source_id":"2402.19366","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:9641aa004f5936ec04d732c92c17f6e213a419cec68e838a9e59c1a8110f5b22","sha256:5dc176d36df55f345e4e6d6b1d7a414f0b64ade580bf825ab5f7af6da8896ea7"],"state_sha256":"fedea567d4758e1555e6fbab120684bf698bca8314e6ad0b8e2842e54d2d6a7a"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5mfhQNK1JLdl9VmSzC+c/gJ9pHct/xXSWnBylwlz5wYT93ETFMB67YVQA9UXnNhCRoD+SYegtMFy/7bZ5TPDCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T09:16:39.508270Z","bundle_sha256":"9e10fddf33881f9fbb8311fb7a24915dfe9c8b8f4bed0c59232b30ade28957a1"}}