{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2026:UMVZRJHCP7SI7WTNUYC4WX6HTT","short_pith_number":"pith:UMVZRJHC","schema_version":"1.0","canonical_sha256":"a32b98a4e27fe48fda6da605cb5fc79cdcbf54997429f1126c5d51b595573b8d","source":{"kind":"arxiv","id":"2607.07089","version":1},"attestation_state":"computed","paper":{"title":"Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.LG","authors_text":"Alan Gany, Bogdan Cautis, Silviu Maniu","submitted_at":"2026-07-08T07:23:09Z","abstract_excerpt":"Relational Deep Learning (RDL) has become a standard methodology for machine learning on relational databases: the database is encoded as a heterogeneous temporal graph in which tuples become nodes and primary-key to foreign-key (PK-FK) dependencies become typed edges, over which a graph neural network is trained for downstream prediction. We study the adversarial robustness of this pipeline. We consider a white-box attacker who knows how the graph is built and the model is trained, reasons about perturbations on the graph, but can only act on the upstream database, by rewiring foreign-key ref"},"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":"2607.07089","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2026-07-08T07:23:09Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"3bb995377a069ec6dd86c9f13c91e4fa7c2d365f2049726774a8220b0af42303","abstract_canon_sha256":"b4c2c9e7ac7dddfae4c4507dfcdf3a5f34c9233881b31dcf27571e728642886a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-09T01:20:14.145092Z","signature_b64":"bIUag6R0ToclZNVUc/ppNkpugTB4rgVXEoEaFKXMrmDEygkeCZut/CAUO4E6nr4pOxMx8Hs+PxQFi7RI40hGDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a32b98a4e27fe48fda6da605cb5fc79cdcbf54997429f1126c5d51b595573b8d","last_reissued_at":"2026-07-09T01:20:14.144687Z","signature_status":"signed_v1","first_computed_at":"2026-07-09T01:20:14.144687Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.LG","authors_text":"Alan Gany, Bogdan Cautis, Silviu Maniu","submitted_at":"2026-07-08T07:23:09Z","abstract_excerpt":"Relational Deep Learning (RDL) has become a standard methodology for machine learning on relational databases: the database is encoded as a heterogeneous temporal graph in which tuples become nodes and primary-key to foreign-key (PK-FK) dependencies become typed edges, over which a graph neural network is trained for downstream prediction. We study the adversarial robustness of this pipeline. We consider a white-box attacker who knows how the graph is built and the model is trained, reasons about perturbations on the graph, but can only act on the upstream database, by rewiring foreign-key ref"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.07089","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/2607.07089/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":"2607.07089","created_at":"2026-07-09T01:20:14.144751+00:00"},{"alias_kind":"arxiv_version","alias_value":"2607.07089v1","created_at":"2026-07-09T01:20:14.144751+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2607.07089","created_at":"2026-07-09T01:20:14.144751+00:00"},{"alias_kind":"pith_short_12","alias_value":"UMVZRJHCP7SI","created_at":"2026-07-09T01:20:14.144751+00:00"},{"alias_kind":"pith_short_16","alias_value":"UMVZRJHCP7SI7WTN","created_at":"2026-07-09T01:20:14.144751+00:00"},{"alias_kind":"pith_short_8","alias_value":"UMVZRJHC","created_at":"2026-07-09T01:20:14.144751+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/UMVZRJHCP7SI7WTNUYC4WX6HTT","json":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT.json","graph_json":"https://pith.science/api/pith-number/UMVZRJHCP7SI7WTNUYC4WX6HTT/graph.json","events_json":"https://pith.science/api/pith-number/UMVZRJHCP7SI7WTNUYC4WX6HTT/events.json","paper":"https://pith.science/paper/UMVZRJHC"},"agent_actions":{"view_html":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT","download_json":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT.json","view_paper":"https://pith.science/paper/UMVZRJHC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2607.07089&json=true","fetch_graph":"https://pith.science/api/pith-number/UMVZRJHCP7SI7WTNUYC4WX6HTT/graph.json","fetch_events":"https://pith.science/api/pith-number/UMVZRJHCP7SI7WTNUYC4WX6HTT/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT/action/storage_attestation","attest_author":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT/action/author_attestation","sign_citation":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT/action/citation_signature","submit_replication":"https://pith.science/pith/UMVZRJHCP7SI7WTNUYC4WX6HTT/action/replication_record"}},"created_at":"2026-07-09T01:20:14.144751+00:00","updated_at":"2026-07-09T01:20:14.144751+00:00"}