{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:D7XBSWW463JYQ2XP27YMWO5TAJ","short_pith_number":"pith:D7XBSWW4","schema_version":"1.0","canonical_sha256":"1fee195adcf6d3886aefd7f0cb3bb3027a2dc31dcda78e71d58b343f3dcc22de","source":{"kind":"arxiv","id":"1910.06261","version":2},"attestation_state":"computed","paper":{"title":"Real-world adversarial attack on MTCNN face detection system","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Aleksandr Petiushko, Edgar Kaziakhmedov, Grigorii Melnikov, Klim Kireev, Mikhail Pautov","submitted_at":"2019-10-14T16:42:09Z","abstract_excerpt":"Recent studies proved that deep learning approaches achieve remarkable results on face detection task. On the other hand, the advances gave rise to a new problem associated with the security of the deep convolutional neural network models unveiling potential risks of DCNNs based applications. Even minor input changes in the digital domain can result in the network being fooled. It was shown then that some deep learning-based face detectors are prone to adversarial attacks not only in a digital domain but also in the real world. In the paper, we investigate the security of the well-known cascad"},"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":"1910.06261","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2019-10-14T16:42:09Z","cross_cats_sorted":["cs.CR","cs.LG"],"title_canon_sha256":"44a1f71ccd4125a43407621b8ab1d1eaedff1ac2c4de6f0607165b194208c02e","abstract_canon_sha256":"9b60919f3123b2514a8163fb9cc93f59df7e86f037f6a8aad7f31e3c621dcfe3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:45:40.709148Z","signature_b64":"AOjZpmPkdqiNRLC24EcFIxf+DO6RiuPKzKZwPZ0elHS6ne2psTzNuwNf2B9nbPMQRwoEjdxX3HmZ5TzoLmP7Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"1fee195adcf6d3886aefd7f0cb3bb3027a2dc31dcda78e71d58b343f3dcc22de","last_reissued_at":"2026-07-05T01:45:40.708770Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:45:40.708770Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Real-world adversarial attack on MTCNN face detection system","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.LG"],"primary_cat":"cs.CV","authors_text":"Aleksandr Petiushko, Edgar Kaziakhmedov, Grigorii Melnikov, Klim Kireev, Mikhail Pautov","submitted_at":"2019-10-14T16:42:09Z","abstract_excerpt":"Recent studies proved that deep learning approaches achieve remarkable results on face detection task. On the other hand, the advances gave rise to a new problem associated with the security of the deep convolutional neural network models unveiling potential risks of DCNNs based applications. Even minor input changes in the digital domain can result in the network being fooled. It was shown then that some deep learning-based face detectors are prone to adversarial attacks not only in a digital domain but also in the real world. In the paper, we investigate the security of the well-known cascad"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.06261","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/1910.06261/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":"1910.06261","created_at":"2026-07-05T01:45:40.708837+00:00"},{"alias_kind":"arxiv_version","alias_value":"1910.06261v2","created_at":"2026-07-05T01:45:40.708837+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.06261","created_at":"2026-07-05T01:45:40.708837+00:00"},{"alias_kind":"pith_short_12","alias_value":"D7XBSWW463JY","created_at":"2026-07-05T01:45:40.708837+00:00"},{"alias_kind":"pith_short_16","alias_value":"D7XBSWW463JYQ2XP","created_at":"2026-07-05T01:45:40.708837+00:00"},{"alias_kind":"pith_short_8","alias_value":"D7XBSWW4","created_at":"2026-07-05T01:45:40.708837+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/D7XBSWW463JYQ2XP27YMWO5TAJ","json":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ.json","graph_json":"https://pith.science/api/pith-number/D7XBSWW463JYQ2XP27YMWO5TAJ/graph.json","events_json":"https://pith.science/api/pith-number/D7XBSWW463JYQ2XP27YMWO5TAJ/events.json","paper":"https://pith.science/paper/D7XBSWW4"},"agent_actions":{"view_html":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ","download_json":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ.json","view_paper":"https://pith.science/paper/D7XBSWW4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1910.06261&json=true","fetch_graph":"https://pith.science/api/pith-number/D7XBSWW463JYQ2XP27YMWO5TAJ/graph.json","fetch_events":"https://pith.science/api/pith-number/D7XBSWW463JYQ2XP27YMWO5TAJ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ/action/storage_attestation","attest_author":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ/action/author_attestation","sign_citation":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ/action/citation_signature","submit_replication":"https://pith.science/pith/D7XBSWW463JYQ2XP27YMWO5TAJ/action/replication_record"}},"created_at":"2026-07-05T01:45:40.708837+00:00","updated_at":"2026-07-05T01:45:40.708837+00:00"}