{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:FT3MBZHZSO6JUGBDOD7QPNAH26","short_pith_number":"pith:FT3MBZHZ","schema_version":"1.0","canonical_sha256":"2cf6c0e4f993bc9a182370ff07b407d7b74f1d613cc0cfafdccdbbbb53a9909d","source":{"kind":"arxiv","id":"2304.01441","version":1},"attestation_state":"computed","paper":{"title":"NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CV"],"primary_cat":"eess.IV","authors_text":"Farinaz Koushanfar, Jung-Woo Chang, Mojan Javaheripi, Nojan Sheybani, Seira Hidano, Shehzeen Samarah Hussain","submitted_at":"2023-04-04T01:29:51Z","abstract_excerpt":"Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based video compression methods are rapidly replacing traditional algorithms and providing state-of-the-art results on edge devices. However, recently developed adversarial attacks demonstrate that digitally crafted perturbations can break the Rate-Distortion relationship of video compression. In this work, we present a real-world LED attack to target video compression frameworks. Our physically realizable attack, dubbed NetFl"},"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":"2304.01441","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.IV","submitted_at":"2023-04-04T01:29:51Z","cross_cats_sorted":["cs.CR","cs.CV"],"title_canon_sha256":"483c55574a11bf4284b63097ecfefd54e805e10dff894d4af5675e3a82b54dbd","abstract_canon_sha256":"6a41214a42492ee2b2ccde73295bb4d7a7724d0236aab902006152dcae33cefb"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:57:40.526622Z","signature_b64":"z7c9jiNLanItWJtN82Wl6VobjPa0ZvNY764/cSdBy6FoA+X72gC5eMbolcJuIuwNtn1PUuglVqERTjIjEE2aCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"2cf6c0e4f993bc9a182370ff07b407d7b74f1d613cc0cfafdccdbbbb53a9909d","last_reissued_at":"2026-07-05T05:57:40.526047Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:57:40.526047Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CV"],"primary_cat":"eess.IV","authors_text":"Farinaz Koushanfar, Jung-Woo Chang, Mojan Javaheripi, Nojan Sheybani, Seira Hidano, Shehzeen Samarah Hussain","submitted_at":"2023-04-04T01:29:51Z","abstract_excerpt":"Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based video compression methods are rapidly replacing traditional algorithms and providing state-of-the-art results on edge devices. However, recently developed adversarial attacks demonstrate that digitally crafted perturbations can break the Rate-Distortion relationship of video compression. In this work, we present a real-world LED attack to target video compression frameworks. Our physically realizable attack, dubbed NetFl"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.01441","kind":"arxiv","version":1},"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/2304.01441/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":"2304.01441","created_at":"2026-07-05T05:57:40.526107+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.01441v1","created_at":"2026-07-05T05:57:40.526107+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.01441","created_at":"2026-07-05T05:57:40.526107+00:00"},{"alias_kind":"pith_short_12","alias_value":"FT3MBZHZSO6J","created_at":"2026-07-05T05:57:40.526107+00:00"},{"alias_kind":"pith_short_16","alias_value":"FT3MBZHZSO6JUGBD","created_at":"2026-07-05T05:57:40.526107+00:00"},{"alias_kind":"pith_short_8","alias_value":"FT3MBZHZ","created_at":"2026-07-05T05:57:40.526107+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/FT3MBZHZSO6JUGBDOD7QPNAH26","json":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26.json","graph_json":"https://pith.science/api/pith-number/FT3MBZHZSO6JUGBDOD7QPNAH26/graph.json","events_json":"https://pith.science/api/pith-number/FT3MBZHZSO6JUGBDOD7QPNAH26/events.json","paper":"https://pith.science/paper/FT3MBZHZ"},"agent_actions":{"view_html":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26","download_json":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26.json","view_paper":"https://pith.science/paper/FT3MBZHZ","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.01441&json=true","fetch_graph":"https://pith.science/api/pith-number/FT3MBZHZSO6JUGBDOD7QPNAH26/graph.json","fetch_events":"https://pith.science/api/pith-number/FT3MBZHZSO6JUGBDOD7QPNAH26/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26/action/timestamp_anchor","attest_storage":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26/action/storage_attestation","attest_author":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26/action/author_attestation","sign_citation":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26/action/citation_signature","submit_replication":"https://pith.science/pith/FT3MBZHZSO6JUGBDOD7QPNAH26/action/replication_record"}},"created_at":"2026-07-05T05:57:40.526107+00:00","updated_at":"2026-07-05T05:57:40.526107+00:00"}