{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2020:IMIACCI7HGXL6BJ3HUINDTVMU3","short_pith_number":"pith:IMIACCI7","schema_version":"1.0","canonical_sha256":"431001091f39aebf053b3d10d1ceaca6f2aa47bea8709f48aef13934e2ed3064","source":{"kind":"arxiv","id":"2010.02387","version":2},"attestation_state":"computed","paper":{"title":"Metadata-Based Detection of Child Sexual Abuse Material","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CY"],"primary_cat":"cs.LG","authors_text":"Hyrum Anderson, Mayana Pereira, Rahul Dodhia, Richard Brown","submitted_at":"2020-10-05T23:10:21Z","abstract_excerpt":"Child Sexual Abuse Media (CSAM) is any visual record of a sexually-explicit activity involving minors. CSAM impacts victims differently from the actual abuse because the distribution never ends, and images are permanent. Machine learning-based solutions can help law enforcement quickly identify CSAM and block digital distribution. However, collecting CSAM imagery to train machine learning models has many ethical and legal constraints, creating a barrier to research development. With such restrictions in place, the development of CSAM machine learning detection systems based on file metadata un"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2010.02387","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-10-05T23:10:21Z","cross_cats_sorted":["cs.CR","cs.CY"],"title_canon_sha256":"845b0a926e00048741f1e09b94e4e9eb93230fb42e4a44647bf1342eddfb14bd","abstract_canon_sha256":"390480cc210b0d31130c02e12666b7bd4bb0e71d73918b1753fcf9eac9e26f0f"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:26:37.419604Z","signature_b64":"45aVyM1qpgI0gVkJXn3xZEEKwN8DWftbm8qZiFm2Fy7oepcj/3tKsr/HKdICZ256Htlr/CGH5hqV53IMJv3wCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"431001091f39aebf053b3d10d1ceaca6f2aa47bea8709f48aef13934e2ed3064","last_reissued_at":"2026-07-05T03:26:37.419109Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:26:37.419109Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Metadata-Based Detection of Child Sexual Abuse Material","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CY"],"primary_cat":"cs.LG","authors_text":"Hyrum Anderson, Mayana Pereira, Rahul Dodhia, Richard Brown","submitted_at":"2020-10-05T23:10:21Z","abstract_excerpt":"Child Sexual Abuse Media (CSAM) is any visual record of a sexually-explicit activity involving minors. CSAM impacts victims differently from the actual abuse because the distribution never ends, and images are permanent. Machine learning-based solutions can help law enforcement quickly identify CSAM and block digital distribution. However, collecting CSAM imagery to train machine learning models has many ethical and legal constraints, creating a barrier to research development. With such restrictions in place, the development of CSAM machine learning detection systems based on file metadata un"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2010.02387","kind":"arxiv","version":2},"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/2010.02387/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2010.02387","created_at":"2026-07-05T03:26:37.419167+00:00"},{"alias_kind":"arxiv_version","alias_value":"2010.02387v2","created_at":"2026-07-05T03:26:37.419167+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2010.02387","created_at":"2026-07-05T03:26:37.419167+00:00"},{"alias_kind":"pith_short_12","alias_value":"IMIACCI7HGXL","created_at":"2026-07-05T03:26:37.419167+00:00"},{"alias_kind":"pith_short_16","alias_value":"IMIACCI7HGXL6BJ3","created_at":"2026-07-05T03:26:37.419167+00:00"},{"alias_kind":"pith_short_8","alias_value":"IMIACCI7","created_at":"2026-07-05T03:26:37.419167+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3","json":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3.json","graph_json":"https://pith.science/api/pith-number/IMIACCI7HGXL6BJ3HUINDTVMU3/graph.json","events_json":"https://pith.science/api/pith-number/IMIACCI7HGXL6BJ3HUINDTVMU3/events.json","paper":"https://pith.science/paper/IMIACCI7"},"agent_actions":{"view_html":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3","download_json":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3.json","view_paper":"https://pith.science/paper/IMIACCI7","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2010.02387&json=true","fetch_graph":"https://pith.science/api/pith-number/IMIACCI7HGXL6BJ3HUINDTVMU3/graph.json","fetch_events":"https://pith.science/api/pith-number/IMIACCI7HGXL6BJ3HUINDTVMU3/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3/action/storage_attestation","attest_author":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3/action/author_attestation","sign_citation":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3/action/citation_signature","submit_replication":"https://pith.science/pith/IMIACCI7HGXL6BJ3HUINDTVMU3/action/replication_record"}},"created_at":"2026-07-05T03:26:37.419167+00:00","updated_at":"2026-07-05T03:26:37.419167+00:00"}