{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:HLYYCHR7QMKSBMIF3PFNJYJRUT","short_pith_number":"pith:HLYYCHR7","canonical_record":{"source":{"id":"2412.01650","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-12-02T15:59:35Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"21c20836e2ebe5eac2b322c896b89f89f85bfb85e8863f27f79c18fb2dabeb4a","abstract_canon_sha256":"47a69b83a5a46354fc8fcc5c4d58bdb436337a2d164c44244b845be11193bd55"},"schema_version":"1.0"},"canonical_sha256":"3af1811e3f831520b105dbcad4e131a4fc1e2a85a8c93dc2af7c50c69714380c","source":{"kind":"arxiv","id":"2412.01650","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01650","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01650v3","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01650","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_12","alias_value":"HLYYCHR7QMKS","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_16","alias_value":"HLYYCHR7QMKSBMIF","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_8","alias_value":"HLYYCHR7","created_at":"2026-07-05T12:06:03Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:HLYYCHR7QMKSBMIF3PFNJYJRUT","target":"record","payload":{"canonical_record":{"source":{"id":"2412.01650","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-12-02T15:59:35Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"21c20836e2ebe5eac2b322c896b89f89f85bfb85e8863f27f79c18fb2dabeb4a","abstract_canon_sha256":"47a69b83a5a46354fc8fcc5c4d58bdb436337a2d164c44244b845be11193bd55"},"schema_version":"1.0"},"canonical_sha256":"3af1811e3f831520b105dbcad4e131a4fc1e2a85a8c93dc2af7c50c69714380c","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:06:03.693912Z","signature_b64":"B5Abvgt2EK/3kRI7JzFageJgaexmiaBRYd3T7Z9qWG1aDlKqCUtwv95kukRDsSsbGcq7tNa+fNa2mG3yLeFSBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3af1811e3f831520b105dbcad4e131a4fc1e2a85a8c93dc2af7c50c69714380c","last_reissued_at":"2026-07-05T12:06:03.693417Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:06:03.693417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2412.01650","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":"2026-07-05T12:06:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xxgmy8yELjbrG2AyXRko2MaUaOfNsAVuCA65xDD0ugtliDbyd2F/+toqQuk4hOWipu40VjHYe0lfCKZUMXJKDg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T09:56:02.924498Z"},"content_sha256":"1bccace4465637e799c436dd1de23277fce89f289a10a22ccc607a498be5e7ed","schema_version":"1.0","event_id":"sha256:1bccace4465637e799c436dd1de23277fce89f289a10a22ccc607a498be5e7ed"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:HLYYCHR7QMKSBMIF3PFNJYJRUT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Chao Lin, Shengmin Xu, Wenhan Dong, Xinlei He, Xinyi Huang","submitted_at":"2024-12-02T15:59:35Z","abstract_excerpt":"Privacy-preserving federated learning (PPFL) aims to train a global model for multiple clients while maintaining their data privacy. However, current PPFL protocols exhibit one or more of the following insufficiencies: considerable degradation in accuracy, the requirement for sharing keys, and cooperation during the key generation or decryption processes. As a mitigation, we develop the first protocol that utilizes neural networks to implement PPFL, as well as incorporating an Aggregatable Hybrid Encryption scheme tailored to the needs of PPFL. We name these networks as Homomorphic Adversarial"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01650","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/2412.01650/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":"2026-07-05T12:06:03Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ghCdwr0K/tBkrmJ8Sme0kP7DUJ/MW7AZfINETTQGHJRziaajbeSIyx4qaufYEBx76+s4mU7XxcF0K7AaBIiNAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-14T09:56:02.924877Z"},"content_sha256":"a1f295670dee7cb3d1bdb2b67c9ca0041d79a5852f6bb1aa898e9b18f5b17c35","schema_version":"1.0","event_id":"sha256:a1f295670dee7cb3d1bdb2b67c9ca0041d79a5852f6bb1aa898e9b18f5b17c35"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/bundle.json","state_url":"https://pith.science/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/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":"2026-07-14T09:56:02Z","links":{"resolver":"https://pith.science/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT","bundle":"https://pith.science/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/bundle.json","state":"https://pith.science/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HLYYCHR7QMKSBMIF3PFNJYJRUT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:HLYYCHR7QMKSBMIF3PFNJYJRUT","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":"47a69b83a5a46354fc8fcc5c4d58bdb436337a2d164c44244b845be11193bd55","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-12-02T15:59:35Z","title_canon_sha256":"21c20836e2ebe5eac2b322c896b89f89f85bfb85e8863f27f79c18fb2dabeb4a"},"schema_version":"1.0","source":{"id":"2412.01650","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2412.01650","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"arxiv_version","alias_value":"2412.01650v3","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2412.01650","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_12","alias_value":"HLYYCHR7QMKS","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_16","alias_value":"HLYYCHR7QMKSBMIF","created_at":"2026-07-05T12:06:03Z"},{"alias_kind":"pith_short_8","alias_value":"HLYYCHR7","created_at":"2026-07-05T12:06:03Z"}],"graph_snapshots":[{"event_id":"sha256:a1f295670dee7cb3d1bdb2b67c9ca0041d79a5852f6bb1aa898e9b18f5b17c35","target":"graph","created_at":"2026-07-05T12:06:03Z","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/2412.01650/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Privacy-preserving federated learning (PPFL) aims to train a global model for multiple clients while maintaining their data privacy. However, current PPFL protocols exhibit one or more of the following insufficiencies: considerable degradation in accuracy, the requirement for sharing keys, and cooperation during the key generation or decryption processes. As a mitigation, we develop the first protocol that utilizes neural networks to implement PPFL, as well as incorporating an Aggregatable Hybrid Encryption scheme tailored to the needs of PPFL. We name these networks as Homomorphic Adversarial","authors_text":"Chao Lin, Shengmin Xu, Wenhan Dong, Xinlei He, Xinyi Huang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-12-02T15:59:35Z","title":"Privacy-Preserving Federated Learning via Homomorphic Adversarial Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2412.01650","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":"sha256:1bccace4465637e799c436dd1de23277fce89f289a10a22ccc607a498be5e7ed","target":"record","created_at":"2026-07-05T12:06:03Z","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":"47a69b83a5a46354fc8fcc5c4d58bdb436337a2d164c44244b845be11193bd55","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2024-12-02T15:59:35Z","title_canon_sha256":"21c20836e2ebe5eac2b322c896b89f89f85bfb85e8863f27f79c18fb2dabeb4a"},"schema_version":"1.0","source":{"id":"2412.01650","kind":"arxiv","version":3}},"canonical_sha256":"3af1811e3f831520b105dbcad4e131a4fc1e2a85a8c93dc2af7c50c69714380c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3af1811e3f831520b105dbcad4e131a4fc1e2a85a8c93dc2af7c50c69714380c","first_computed_at":"2026-07-05T12:06:03.693417Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T12:06:03.693417Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"B5Abvgt2EK/3kRI7JzFageJgaexmiaBRYd3T7Z9qWG1aDlKqCUtwv95kukRDsSsbGcq7tNa+fNa2mG3yLeFSBw==","signature_status":"signed_v1","signed_at":"2026-07-05T12:06:03.693912Z","signed_message":"canonical_sha256_bytes"},"source_id":"2412.01650","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1bccace4465637e799c436dd1de23277fce89f289a10a22ccc607a498be5e7ed","sha256:a1f295670dee7cb3d1bdb2b67c9ca0041d79a5852f6bb1aa898e9b18f5b17c35"],"state_sha256":"6c241565c2604aa7cf8b0688cd8c1e4ad87d29588e08f8710c97ca287f9fb741"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"V5XOhK1CTuBhqY1GN3tY8+uHiUe2QGl9IyPiO0VLOZbTsHiqys4URo5clxAvz0G8SKdroCgQcSTQNUTkTS71Cg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-14T09:56:02.929325Z","bundle_sha256":"07617bb331b709be89b36881e4371d5c4a226b9f33e6151a7e69f481f52e151c"}}