{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:5NZNXQCEPAJP2WVQZRNZKJ675R","short_pith_number":"pith:5NZNXQCE","canonical_record":{"source":{"id":"2205.06117","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-12T14:31:54Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"fcdc348f416d9d25f55d103875f13b1e76e52c3c8c115e8806ea929a81328352","abstract_canon_sha256":"3378fab302dfeaa594236f7e2c6bc6b0724dc41ff81dd59078cd85e18780538a"},"schema_version":"1.0"},"canonical_sha256":"eb72dbc0447812fd5ab0cc5b9527dfec6b5c9339017e7c49f264de0154160543","source":{"kind":"arxiv","id":"2205.06117","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.06117","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"arxiv_version","alias_value":"2205.06117v1","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.06117","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_12","alias_value":"5NZNXQCEPAJP","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_16","alias_value":"5NZNXQCEPAJP2WVQ","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_8","alias_value":"5NZNXQCE","created_at":"2026-07-05T04:22:45Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:5NZNXQCEPAJP2WVQZRNZKJ675R","target":"record","payload":{"canonical_record":{"source":{"id":"2205.06117","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-12T14:31:54Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"fcdc348f416d9d25f55d103875f13b1e76e52c3c8c115e8806ea929a81328352","abstract_canon_sha256":"3378fab302dfeaa594236f7e2c6bc6b0724dc41ff81dd59078cd85e18780538a"},"schema_version":"1.0"},"canonical_sha256":"eb72dbc0447812fd5ab0cc5b9527dfec6b5c9339017e7c49f264de0154160543","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:22:45.604452Z","signature_b64":"EbUXoj/kxUI9lucJAk3H2uk6cawZ6BEc7iEFD9MUrcfdTcENx/MvKUyfsyCflg9TAPmtN3hjmTJgiG6T0MuVDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"eb72dbc0447812fd5ab0cc5b9527dfec6b5c9339017e7c49f264de0154160543","last_reissued_at":"2026-07-05T04:22:45.603974Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:22:45.603974Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2205.06117","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:22:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2wsrq3jMGKce8e3vJYGQv13ROisAkVIiKhsjIPd/7/pOXTHtGH7N7IiImlMxpZ921A9okvugiMk+14KBJYN8Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T16:32:30.659941Z"},"content_sha256":"65f41b9646377ab13cf7961fdfdc5eb9ddd5e0f2a39b95eb429e261d5f4fd76d","schema_version":"1.0","event_id":"sha256:65f41b9646377ab13cf7961fdfdc5eb9ddd5e0f2a39b95eb429e261d5f4fd76d"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:5NZNXQCEPAJP2WVQZRNZKJ675R","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Secure Aggregation for Federated Learning in Flower","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Daniel J. Beutel, Kwing Hei Li, Nicholas D. Lane, Pedro Porto Buarque de Gusm\\~ao","submitted_at":"2022-05-12T14:31:54Z","abstract_excerpt":"Federated Learning (FL) allows parties to learn a shared prediction model by delegating the training computation to clients and aggregating all the separately trained models on the server. To prevent private information being inferred from local models, Secure Aggregation (SA) protocols are used to ensure that the server is unable to inspect individual trained models as it aggregates them. However, current implementations of SA in FL frameworks have limitations, including vulnerability to client dropouts or configuration difficulties.\n  In this paper, we present Salvia, an implementation of SA"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.06117","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/2205.06117/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":"2026-07-05T04:22:45Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ysq6nzV49pxViu0cfUirgRHk/NVNhMYudbCnGvZMXPHaDmal8vBe43QQ3eM14ntczo67yH9OlmLAYkOZiwmECA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-18T16:32:30.660444Z"},"content_sha256":"d2e690b4c7bc6027aae5a833a70bdb3f2e3a70f31b63a8f61b2f1ced25c5b39f","schema_version":"1.0","event_id":"sha256:d2e690b4c7bc6027aae5a833a70bdb3f2e3a70f31b63a8f61b2f1ced25c5b39f"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/bundle.json","state_url":"https://pith.science/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/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":"2026-08-18T16:32:30Z","links":{"resolver":"https://pith.science/pith/5NZNXQCEPAJP2WVQZRNZKJ675R","bundle":"https://pith.science/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/bundle.json","state":"https://pith.science/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/state.json","well_known_bundle":"https://pith.science/.well-known/pith/5NZNXQCEPAJP2WVQZRNZKJ675R/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:5NZNXQCEPAJP2WVQZRNZKJ675R","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":"3378fab302dfeaa594236f7e2c6bc6b0724dc41ff81dd59078cd85e18780538a","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-12T14:31:54Z","title_canon_sha256":"fcdc348f416d9d25f55d103875f13b1e76e52c3c8c115e8806ea929a81328352"},"schema_version":"1.0","source":{"id":"2205.06117","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2205.06117","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"arxiv_version","alias_value":"2205.06117v1","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2205.06117","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_12","alias_value":"5NZNXQCEPAJP","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_16","alias_value":"5NZNXQCEPAJP2WVQ","created_at":"2026-07-05T04:22:45Z"},{"alias_kind":"pith_short_8","alias_value":"5NZNXQCE","created_at":"2026-07-05T04:22:45Z"}],"graph_snapshots":[{"event_id":"sha256:d2e690b4c7bc6027aae5a833a70bdb3f2e3a70f31b63a8f61b2f1ced25c5b39f","target":"graph","created_at":"2026-07-05T04:22:45Z","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/2205.06117/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Federated Learning (FL) allows parties to learn a shared prediction model by delegating the training computation to clients and aggregating all the separately trained models on the server. To prevent private information being inferred from local models, Secure Aggregation (SA) protocols are used to ensure that the server is unable to inspect individual trained models as it aggregates them. However, current implementations of SA in FL frameworks have limitations, including vulnerability to client dropouts or configuration difficulties.\n  In this paper, we present Salvia, an implementation of SA","authors_text":"Daniel J. Beutel, Kwing Hei Li, Nicholas D. Lane, Pedro Porto Buarque de Gusm\\~ao","cross_cats":["cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-12T14:31:54Z","title":"Secure Aggregation for Federated Learning in Flower"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2205.06117","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":"sha256:65f41b9646377ab13cf7961fdfdc5eb9ddd5e0f2a39b95eb429e261d5f4fd76d","target":"record","created_at":"2026-07-05T04:22:45Z","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":"3378fab302dfeaa594236f7e2c6bc6b0724dc41ff81dd59078cd85e18780538a","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2022-05-12T14:31:54Z","title_canon_sha256":"fcdc348f416d9d25f55d103875f13b1e76e52c3c8c115e8806ea929a81328352"},"schema_version":"1.0","source":{"id":"2205.06117","kind":"arxiv","version":1}},"canonical_sha256":"eb72dbc0447812fd5ab0cc5b9527dfec6b5c9339017e7c49f264de0154160543","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"eb72dbc0447812fd5ab0cc5b9527dfec6b5c9339017e7c49f264de0154160543","first_computed_at":"2026-07-05T04:22:45.603974Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:22:45.603974Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"EbUXoj/kxUI9lucJAk3H2uk6cawZ6BEc7iEFD9MUrcfdTcENx/MvKUyfsyCflg9TAPmtN3hjmTJgiG6T0MuVDA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:22:45.604452Z","signed_message":"canonical_sha256_bytes"},"source_id":"2205.06117","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:65f41b9646377ab13cf7961fdfdc5eb9ddd5e0f2a39b95eb429e261d5f4fd76d","sha256:d2e690b4c7bc6027aae5a833a70bdb3f2e3a70f31b63a8f61b2f1ced25c5b39f"],"state_sha256":"ac50a3a8e4d7033d7c47441de0d1c1d530625fe6059826ede15486fbae88c111"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"NNt65aoDB8PZNAAkVOGr/GE+T8Mj15dD1u7zK4BHNDTy7Sxe81RdM5240tUb1C1EZFqZWfuUJ9dlsmMWewXrDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-18T16:32:30.665103Z","bundle_sha256":"8e6fb68adb70b29de9c68d7df7b7a2da3f88bd116580cbe2400345af5e1775e8"}}