{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:Z3HKZ6JOLBEOYBMAMSUKT5JMLM","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":"9b95482f942de4a72aeb56d95c677f06f540724099cb0cf67ad320848c37c4db","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T20:14:38Z","title_canon_sha256":"0406522139dd5215588b0f4a1d8763ac5cf9bf22c5ccfa9f2def4f7385595705"},"schema_version":"1.0","source":{"id":"2506.00701","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2506.00701","created_at":"2026-07-05T11:13:38Z"},{"alias_kind":"arxiv_version","alias_value":"2506.00701v1","created_at":"2026-07-05T11:13:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.00701","created_at":"2026-07-05T11:13:38Z"},{"alias_kind":"pith_short_12","alias_value":"Z3HKZ6JOLBEO","created_at":"2026-07-05T11:13:38Z"},{"alias_kind":"pith_short_16","alias_value":"Z3HKZ6JOLBEOYBMA","created_at":"2026-07-05T11:13:38Z"},{"alias_kind":"pith_short_8","alias_value":"Z3HKZ6JO","created_at":"2026-07-05T11:13:38Z"}],"graph_snapshots":[{"event_id":"sha256:d4ac1abf6552740c5b62ea89353ba9d35eed10c0532d2e563ae8f48aed80248a","target":"graph","created_at":"2026-07-05T11:13:38Z","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/2506.00701/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Determining whether a dataset was part of a machine learning model's training data pool can reveal privacy vulnerabilities, a challenge often addressed through membership inference attacks (MIAs). Traditional MIAs typically require access to model internals or rely on computationally intensive shadow models. This paper proposes an efficient, interpretable and principled Bayesian inference method for membership inference. By analyzing post-hoc metrics such as prediction error, confidence (entropy), perturbation magnitude, and dataset statistics from a trained ML model, our approach computes pos","authors_text":"Yongchao Huang","cross_cats":["cs.AI"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T20:14:38Z","title":"Bayesian Inference of Training Dataset Membership"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.00701","kind":"arxiv","version":1},"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":"sha256:981dcb0ce313ed8897d6564cc15c1e3f285ead9d4228b639af054f47169191df","target":"record","created_at":"2026-07-05T11:13:38Z","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":"9b95482f942de4a72aeb56d95c677f06f540724099cb0cf67ad320848c37c4db","cross_cats_sorted":["cs.AI"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2025-05-31T20:14:38Z","title_canon_sha256":"0406522139dd5215588b0f4a1d8763ac5cf9bf22c5ccfa9f2def4f7385595705"},"schema_version":"1.0","source":{"id":"2506.00701","kind":"arxiv","version":1}},"canonical_sha256":"ceceacf92e5848ec058064a8a9f52c5b35785ca21642ac4f45c187f8f3853b21","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ceceacf92e5848ec058064a8a9f52c5b35785ca21642ac4f45c187f8f3853b21","first_computed_at":"2026-07-05T11:13:38.947080Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:13:38.947080Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"6fQa4TMDN10kYMlEMOG+ma52z1bzQVpoXPUlpFkrVZDwpNvN3QTEhpkmTBohC3K2AFWgICBAETZ/cggXQ3hnCw==","signature_status":"signed_v1","signed_at":"2026-07-05T11:13:38.947643Z","signed_message":"canonical_sha256_bytes"},"source_id":"2506.00701","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:981dcb0ce313ed8897d6564cc15c1e3f285ead9d4228b639af054f47169191df","sha256:d4ac1abf6552740c5b62ea89353ba9d35eed10c0532d2e563ae8f48aed80248a"],"state_sha256":"0afec35df69d7ac34053eaa9ff3e4ce710b49c4bbeb8c136d789760fcb53ab6e"}