{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:XQTKMK7FHFHCFJ5HKIAHT7ZNGZ","short_pith_number":"pith:XQTKMK7F","canonical_record":{"source":{"id":"2205.11584","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T19:26:12Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"45cbc08cd964ce16b87a7cd40a42d08207f4fa913d50af142a50e8ace307815f","abstract_canon_sha256":"20f30cebc3bd7b6082dacb034a2b51b99f1380e5cd076f5d2c992c9d957ea2a8"},"schema_version":"1.0"},"canonical_sha256":"bc26a62be5394e22a7a7520079ff2d365c5373f9691212cb7a222dfb329c906a","source":{"kind":"arxiv","id":"2205.11584","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11584","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11584v2","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11584","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_12","alias_value":"XQTKMK7FHFHC","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_16","alias_value":"XQTKMK7FHFHCFJ5H","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_8","alias_value":"XQTKMK7F","created_at":"2026-07-05T04:51:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:XQTKMK7FHFHCFJ5HKIAHT7ZNGZ","target":"record","payload":{"canonical_record":{"source":{"id":"2205.11584","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T19:26:12Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"45cbc08cd964ce16b87a7cd40a42d08207f4fa913d50af142a50e8ace307815f","abstract_canon_sha256":"20f30cebc3bd7b6082dacb034a2b51b99f1380e5cd076f5d2c992c9d957ea2a8"},"schema_version":"1.0"},"canonical_sha256":"bc26a62be5394e22a7a7520079ff2d365c5373f9691212cb7a222dfb329c906a","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:51:57.156625Z","signature_b64":"z5sLx6tw+u1XYjwrJH0a2GcxQUik9lT931K+9ahVZlh20/+xxE4BpiDnXJ/MoYdsUp06ek//KLD1J1MBnUEDDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bc26a62be5394e22a7a7520079ff2d365c5373f9691212cb7a222dfb329c906a","last_reissued_at":"2026-07-05T04:51:57.156140Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:51:57.156140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.11584","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:51:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Y69eQ7AnoHK4GMR+oOLBwoNXJBgs8qGTNQpn9uFQKNTB48tEeOQ8907TMjBotgVuJEb96mlQtTjSIVo10fHSDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:11:56.196949Z"},"content_sha256":"2f6a0e37ca1772b0d12d00269618669512738b5cc7b7eff4f9bc2919a3032eae","schema_version":"1.0","event_id":"sha256:2f6a0e37ca1772b0d12d00269618669512738b5cc7b7eff4f9bc2919a3032eae"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:XQTKMK7FHFHCFJ5HKIAHT7ZNGZ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Anderson Nascimento, Golnoosh Farnadi, Martine De Cock, Nicola Neophytou, Sikha Pentyala","submitted_at":"2022-05-23T19:26:12Z","abstract_excerpt":"Group fairness ensures that the outcome of machine learning (ML) based decision making systems are not biased towards a certain group of people defined by a sensitive attribute such as gender or ethnicity. Achieving group fairness in Federated Learning (FL) is challenging because mitigating bias inherently requires using the sensitive attribute values of all clients, while FL is aimed precisely at protecting privacy by not giving access to the clients' data. As we show in this paper, this conflict between fairness and privacy in FL can be resolved by combining FL with Secure Multiparty Computa"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11584","kind":"arxiv","version":2},"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/2205.11584/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":"2026-07-05T04:51:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"mlFOx2d/qTADvDSHsDMuUuzQ5Lve+ifmoijfWDi0YKWXmGclVffUXK/umUOzjo0i3kQasHiSBED+Y0WAO7ywBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T13:11:56.197610Z"},"content_sha256":"0c5c277b679ad575baab4af144dd7c7e50547123c071d0151edd8ade225dec52","schema_version":"1.0","event_id":"sha256:0c5c277b679ad575baab4af144dd7c7e50547123c071d0151edd8ade225dec52"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/bundle.json","state_url":"https://pith.science/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/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":"2026-08-08T13:11:56Z","links":{"resolver":"https://pith.science/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ","bundle":"https://pith.science/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/bundle.json","state":"https://pith.science/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/XQTKMK7FHFHCFJ5HKIAHT7ZNGZ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:XQTKMK7FHFHCFJ5HKIAHT7ZNGZ","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":"20f30cebc3bd7b6082dacb034a2b51b99f1380e5cd076f5d2c992c9d957ea2a8","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T19:26:12Z","title_canon_sha256":"45cbc08cd964ce16b87a7cd40a42d08207f4fa913d50af142a50e8ace307815f"},"schema_version":"1.0","source":{"id":"2205.11584","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.11584","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"arxiv_version","alias_value":"2205.11584v2","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.11584","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_12","alias_value":"XQTKMK7FHFHC","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_16","alias_value":"XQTKMK7FHFHCFJ5H","created_at":"2026-07-05T04:51:57Z"},{"alias_kind":"pith_short_8","alias_value":"XQTKMK7F","created_at":"2026-07-05T04:51:57Z"}],"graph_snapshots":[{"event_id":"sha256:0c5c277b679ad575baab4af144dd7c7e50547123c071d0151edd8ade225dec52","target":"graph","created_at":"2026-07-05T04:51:57Z","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/2205.11584/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Group fairness ensures that the outcome of machine learning (ML) based decision making systems are not biased towards a certain group of people defined by a sensitive attribute such as gender or ethnicity. Achieving group fairness in Federated Learning (FL) is challenging because mitigating bias inherently requires using the sensitive attribute values of all clients, while FL is aimed precisely at protecting privacy by not giving access to the clients' data. As we show in this paper, this conflict between fairness and privacy in FL can be resolved by combining FL with Secure Multiparty Computa","authors_text":"Anderson Nascimento, Golnoosh Farnadi, Martine De Cock, Nicola Neophytou, Sikha Pentyala","cross_cats":["cs.CR"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T19:26:12Z","title":"PrivFairFL: Privacy-Preserving Group Fairness in Federated Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.11584","kind":"arxiv","version":2},"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":"sha256:2f6a0e37ca1772b0d12d00269618669512738b5cc7b7eff4f9bc2919a3032eae","target":"record","created_at":"2026-07-05T04:51:57Z","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":"20f30cebc3bd7b6082dacb034a2b51b99f1380e5cd076f5d2c992c9d957ea2a8","cross_cats_sorted":["cs.CR"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2022-05-23T19:26:12Z","title_canon_sha256":"45cbc08cd964ce16b87a7cd40a42d08207f4fa913d50af142a50e8ace307815f"},"schema_version":"1.0","source":{"id":"2205.11584","kind":"arxiv","version":2}},"canonical_sha256":"bc26a62be5394e22a7a7520079ff2d365c5373f9691212cb7a222dfb329c906a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"bc26a62be5394e22a7a7520079ff2d365c5373f9691212cb7a222dfb329c906a","first_computed_at":"2026-07-05T04:51:57.156140Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:51:57.156140Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"z5sLx6tw+u1XYjwrJH0a2GcxQUik9lT931K+9ahVZlh20/+xxE4BpiDnXJ/MoYdsUp06ek//KLD1J1MBnUEDDg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:51:57.156625Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.11584","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:2f6a0e37ca1772b0d12d00269618669512738b5cc7b7eff4f9bc2919a3032eae","sha256:0c5c277b679ad575baab4af144dd7c7e50547123c071d0151edd8ade225dec52"],"state_sha256":"2fccf3a87e644464bdf1b4097bf7ffa1fa51e8916416ace015b0fab52173af47"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"fumPa0R95zJBrozkQkks/MDGz7WDKGxZCPO0wzQhB8vz2bAm47uKdNTwl/Ih5hijtb5yBeP/6Qh/OZ32Cse2AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T13:11:56.201927Z","bundle_sha256":"20026e9332ffd60692075c2d71b92533de70d846642338009c285acf3d768e18"}}