{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:L4BMUQEPSK6FJGWF2W2UBRJ4WV","short_pith_number":"pith:L4BMUQEP","schema_version":"1.0","canonical_sha256":"5f02ca408f92bc549ac5d5b540c53cb5738ced6c842559f968c4743ed3ba0d1e","source":{"kind":"arxiv","id":"2409.02483","version":5},"attestation_state":"computed","paper":{"title":"TASAR: Transfer-based Attack on Skeletal Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Ajian Liu, Baiqi Wu, He Wang, Meng Wang, Ruixuan Zhang, Xiaoshuai Hao, Xingxing Wei, Yunfeng Diao","submitted_at":"2024-09-04T07:20:01Z","abstract_excerpt":"Skeletal sequence data, as a widely employed representation of human actions, are crucial in Human Activity Recognition (HAR). Recently, adversarial attacks have been proposed in this area, which exposes potential security concerns, and more importantly provides a good tool for model robustness test. Within this research, transfer-based attack is an important tool as it mimics the real-world scenario where an attacker has no knowledge of the target model, but is under-explored in Skeleton-based HAR (S-HAR). Consequently, existing S-HAR attacks exhibit weak adversarial transferability and the r"},"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":"2409.02483","kind":"arxiv","version":5},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CV","submitted_at":"2024-09-04T07:20:01Z","cross_cats_sorted":["cs.AI"],"title_canon_sha256":"210feeb3dd3f421ed11a03d145fb73177410d6834c6f960f76f86282bd6a1a70","abstract_canon_sha256":"57488c7d28572771cca11655692d517fa817b2a2b1731b2f4007c7f4183dddc3"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:13:03.447150Z","signature_b64":"JTJidWpD5NwzvrRi8OJ8wVVsteezd+PU6mZ3AUIHT92IiqL5jE8L5LiadwH1bxLXhg0hejaJ2/vKdIEUl7nDBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f02ca408f92bc549ac5d5b540c53cb5738ced6c842559f968c4743ed3ba0d1e","last_reissued_at":"2026-07-05T10:13:03.446689Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:13:03.446689Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"TASAR: Transfer-based Attack on Skeletal Action Recognition","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI"],"primary_cat":"cs.CV","authors_text":"Ajian Liu, Baiqi Wu, He Wang, Meng Wang, Ruixuan Zhang, Xiaoshuai Hao, Xingxing Wei, Yunfeng Diao","submitted_at":"2024-09-04T07:20:01Z","abstract_excerpt":"Skeletal sequence data, as a widely employed representation of human actions, are crucial in Human Activity Recognition (HAR). Recently, adversarial attacks have been proposed in this area, which exposes potential security concerns, and more importantly provides a good tool for model robustness test. Within this research, transfer-based attack is an important tool as it mimics the real-world scenario where an attacker has no knowledge of the target model, but is under-explored in Skeleton-based HAR (S-HAR). Consequently, existing S-HAR attacks exhibit weak adversarial transferability and the r"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2409.02483","kind":"arxiv","version":5},"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/2409.02483/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":"2409.02483","created_at":"2026-07-05T10:13:03.446740+00:00"},{"alias_kind":"arxiv_version","alias_value":"2409.02483v5","created_at":"2026-07-05T10:13:03.446740+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2409.02483","created_at":"2026-07-05T10:13:03.446740+00:00"},{"alias_kind":"pith_short_12","alias_value":"L4BMUQEPSK6F","created_at":"2026-07-05T10:13:03.446740+00:00"},{"alias_kind":"pith_short_16","alias_value":"L4BMUQEPSK6FJGWF","created_at":"2026-07-05T10:13:03.446740+00:00"},{"alias_kind":"pith_short_8","alias_value":"L4BMUQEP","created_at":"2026-07-05T10:13:03.446740+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":1,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2606.13022","citing_title":"Quality-Preserving Imperceptible Adversarial Attack on Skeleton-based Human Action Recognition","ref_index":2,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV","json":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV.json","graph_json":"https://pith.science/api/pith-number/L4BMUQEPSK6FJGWF2W2UBRJ4WV/graph.json","events_json":"https://pith.science/api/pith-number/L4BMUQEPSK6FJGWF2W2UBRJ4WV/events.json","paper":"https://pith.science/paper/L4BMUQEP"},"agent_actions":{"view_html":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV","download_json":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV.json","view_paper":"https://pith.science/paper/L4BMUQEP","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2409.02483&json=true","fetch_graph":"https://pith.science/api/pith-number/L4BMUQEPSK6FJGWF2W2UBRJ4WV/graph.json","fetch_events":"https://pith.science/api/pith-number/L4BMUQEPSK6FJGWF2W2UBRJ4WV/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV/action/timestamp_anchor","attest_storage":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV/action/storage_attestation","attest_author":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV/action/author_attestation","sign_citation":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV/action/citation_signature","submit_replication":"https://pith.science/pith/L4BMUQEPSK6FJGWF2W2UBRJ4WV/action/replication_record"}},"created_at":"2026-07-05T10:13:03.446740+00:00","updated_at":"2026-07-05T10:13:03.446740+00:00"}