{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:O42EHP5KTYP5TJXU2T2C4FGDKG","short_pith_number":"pith:O42EHP5K","canonical_record":{"source":{"id":"2009.00203","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2020-09-01T03:24:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"438cdb23171dcd2f22e56a8a699c7d9d9cd1348dd859bb99e54fde676de9a0b4","abstract_canon_sha256":"6a7af582e75f9dd7dc047753f8bc8789d1f259326d8b591829f65bfbffe0451f"},"schema_version":"1.0"},"canonical_sha256":"773443bfaa9e1fd9a6f4d4f42e14c351aedb9d2f6f28e6a85a9183ea3325758d","source":{"kind":"arxiv","id":"2009.00203","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.00203","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"arxiv_version","alias_value":"2009.00203v3","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.00203","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_12","alias_value":"O42EHP5KTYP5","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_16","alias_value":"O42EHP5KTYP5TJXU","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_8","alias_value":"O42EHP5K","created_at":"2026-07-05T07:24:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:O42EHP5KTYP5TJXU2T2C4FGDKG","target":"record","payload":{"canonical_record":{"source":{"id":"2009.00203","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2020-09-01T03:24:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"438cdb23171dcd2f22e56a8a699c7d9d9cd1348dd859bb99e54fde676de9a0b4","abstract_canon_sha256":"6a7af582e75f9dd7dc047753f8bc8789d1f259326d8b591829f65bfbffe0451f"},"schema_version":"1.0"},"canonical_sha256":"773443bfaa9e1fd9a6f4d4f42e14c351aedb9d2f6f28e6a85a9183ea3325758d","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:24:44.396376Z","signature_b64":"JVCor73c+cee/oifW64xjrOdW5k9H9bL0fCmft5DZG1kbP8pcUs9kD76TXBSpTOUF0+6vz1iQ7TeQwckyg5/Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"773443bfaa9e1fd9a6f4d4f42e14c351aedb9d2f6f28e6a85a9183ea3325758d","last_reissued_at":"2026-07-05T07:24:44.395977Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:24:44.395977Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2009.00203","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":"2026-07-05T07:24:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5Y0A/EpjhC6chLVj3kU7m6ZboKiLGDmHCzfqfRF7fGUqhv8ImtxBqnFWvzqEAyl+z0pSYZf5GYiHRQl+2QEuAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:53:01.446733Z"},"content_sha256":"8fb25d3e2d7468edaabfc3d5dca659d381f7dc5a5cc2b9a606de089c8bddaf9a","schema_version":"1.0","event_id":"sha256:8fb25d3e2d7468edaabfc3d5dca659d381f7dc5a5cc2b9a606de089c8bddaf9a"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:O42EHP5KTYP5TJXU2T2C4FGDKG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Ang Li, Binghui Wang, Hai Li, Meng Pang, Minhua Lin, Pan Zhou, Tianxiang Zhou, Yiran Chen","submitted_at":"2020-09-01T03:24:51Z","abstract_excerpt":"Graph neural network (GNN), the mainstream method to learn on graph data, is vulnerable to graph evasion attacks, where an attacker slightly perturbing the graph structure can fool trained GNN models. Existing work has at least one of the following drawbacks: 1) limited to directly attack two-layer GNNs; 2) inefficient; and 3) impractical, as they need to know full or part of GNN model parameters.\n  We address the above drawbacks and propose an influence-based \\emph{efficient, direct, and restricted black-box} evasion attack to \\emph{any-layer} GNNs. Specifically, we first introduce two influe"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.00203","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/2009.00203/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":"2026-07-05T07:24:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qx4BQyb7WVQv5y5RMWI+Y/s725pJzzoSm2Ac9FtAphFKuyf0uYvHE1ALlRVKnPxTTXuZ5yj/aWAeJ2UN5r8UCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T18:53:01.447298Z"},"content_sha256":"ea0eb5ee02b2b9c63ff48b1ffa029ba910f5db3f5052962d5070ccdfee6f3f3d","schema_version":"1.0","event_id":"sha256:ea0eb5ee02b2b9c63ff48b1ffa029ba910f5db3f5052962d5070ccdfee6f3f3d"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/bundle.json","state_url":"https://pith.science/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/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":"2026-08-05T18:53:01Z","links":{"resolver":"https://pith.science/pith/O42EHP5KTYP5TJXU2T2C4FGDKG","bundle":"https://pith.science/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/bundle.json","state":"https://pith.science/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/O42EHP5KTYP5TJXU2T2C4FGDKG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:O42EHP5KTYP5TJXU2T2C4FGDKG","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":"6a7af582e75f9dd7dc047753f8bc8789d1f259326d8b591829f65bfbffe0451f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2020-09-01T03:24:51Z","title_canon_sha256":"438cdb23171dcd2f22e56a8a699c7d9d9cd1348dd859bb99e54fde676de9a0b4"},"schema_version":"1.0","source":{"id":"2009.00203","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2009.00203","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"arxiv_version","alias_value":"2009.00203v3","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2009.00203","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_12","alias_value":"O42EHP5KTYP5","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_16","alias_value":"O42EHP5KTYP5TJXU","created_at":"2026-07-05T07:24:44Z"},{"alias_kind":"pith_short_8","alias_value":"O42EHP5K","created_at":"2026-07-05T07:24:44Z"}],"graph_snapshots":[{"event_id":"sha256:ea0eb5ee02b2b9c63ff48b1ffa029ba910f5db3f5052962d5070ccdfee6f3f3d","target":"graph","created_at":"2026-07-05T07:24:44Z","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/2009.00203/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph neural network (GNN), the mainstream method to learn on graph data, is vulnerable to graph evasion attacks, where an attacker slightly perturbing the graph structure can fool trained GNN models. Existing work has at least one of the following drawbacks: 1) limited to directly attack two-layer GNNs; 2) inefficient; and 3) impractical, as they need to know full or part of GNN model parameters.\n  We address the above drawbacks and propose an influence-based \\emph{efficient, direct, and restricted black-box} evasion attack to \\emph{any-layer} GNNs. Specifically, we first introduce two influe","authors_text":"Ang Li, Binghui Wang, Hai Li, Meng Pang, Minhua Lin, Pan Zhou, Tianxiang Zhou, Yiran Chen","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2020-09-01T03:24:51Z","title":"Efficient, Direct, and Restricted Black-Box Graph Evasion Attacks to Any-Layer Graph Neural Networks via Influence Function"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2009.00203","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":"sha256:8fb25d3e2d7468edaabfc3d5dca659d381f7dc5a5cc2b9a606de089c8bddaf9a","target":"record","created_at":"2026-07-05T07:24:44Z","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":"6a7af582e75f9dd7dc047753f8bc8789d1f259326d8b591829f65bfbffe0451f","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2020-09-01T03:24:51Z","title_canon_sha256":"438cdb23171dcd2f22e56a8a699c7d9d9cd1348dd859bb99e54fde676de9a0b4"},"schema_version":"1.0","source":{"id":"2009.00203","kind":"arxiv","version":3}},"canonical_sha256":"773443bfaa9e1fd9a6f4d4f42e14c351aedb9d2f6f28e6a85a9183ea3325758d","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"773443bfaa9e1fd9a6f4d4f42e14c351aedb9d2f6f28e6a85a9183ea3325758d","first_computed_at":"2026-07-05T07:24:44.395977Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:24:44.395977Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"JVCor73c+cee/oifW64xjrOdW5k9H9bL0fCmft5DZG1kbP8pcUs9kD76TXBSpTOUF0+6vz1iQ7TeQwckyg5/Dg==","signature_status":"signed_v1","signed_at":"2026-07-05T07:24:44.396376Z","signed_message":"canonical_sha256_bytes"},"source_id":"2009.00203","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8fb25d3e2d7468edaabfc3d5dca659d381f7dc5a5cc2b9a606de089c8bddaf9a","sha256:ea0eb5ee02b2b9c63ff48b1ffa029ba910f5db3f5052962d5070ccdfee6f3f3d"],"state_sha256":"ef65bee3e3c7831a469342194aa4d1a0b8456f89aa7db0187a9fa380a2f33451"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ODfCYyLN3z5kCle+Hfl3GpL9bjH9W/thGNQYFmFp667fG74tYa0OdMgBI+hU//M8MYc+FnjmGbdrx8z/NVIyDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T18:53:01.451309Z","bundle_sha256":"466aa8e010b10a683ab9146228a032667c2182a3f28b46f31186507318ecf570"}}