{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:U6G6HOKTPYG2TNNGEY7C44NYQG","short_pith_number":"pith:U6G6HOKT","schema_version":"1.0","canonical_sha256":"a78de3b9537e0da9b5a6263e2e71b8818811c4fb357bc9daf4b33aedfa3dc776","source":{"kind":"arxiv","id":"2304.05836","version":3},"attestation_state":"computed","paper":{"title":"A Game-theoretic Framework for Privacy-preserving Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.GT"],"primary_cat":"cs.LG","authors_text":"Kai Chen, Lixin Fan, Qiang Yang, Siwei Wang, Wenjie Li, Xiaojin Zhang","submitted_at":"2023-04-11T14:20:31Z","abstract_excerpt":"In federated learning, benign participants aim to optimize a global model collaboratively. However, the risk of \\textit{privacy leakage} cannot be ignored in the presence of \\textit{semi-honest} adversaries. Existing research has focused either on designing protection mechanisms or on inventing attacking mechanisms. While the battle between defenders and attackers seems never-ending, we are concerned with one critical question: is it possible to prevent potential attacks in advance? To address this, we propose the first game-theoretic framework that considers both FL defenders and attackers in"},"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":"2304.05836","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2023-04-11T14:20:31Z","cross_cats_sorted":["cs.AI","cs.CR","cs.GT"],"title_canon_sha256":"c7804c221aee130f4bf6662502f6c720dafbda7377ce11f4d5002f95f00faedd","abstract_canon_sha256":"3afbd571fdb732c80270c8fbb38aee4d11a4ed4df7c639879fccbe96a11cfe8d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:50:00.730126Z","signature_b64":"UTwwNSnlp9fIPwYM/HhhT+UmOn3DOIv9Zo1IdeHdM33XwHO4Z+LdlEUWzS52MWEqMFBDDIVEueb+jPzIdMnjDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a78de3b9537e0da9b5a6263e2e71b8818811c4fb357bc9daf4b33aedfa3dc776","last_reissued_at":"2026-07-05T07:50:00.729710Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:50:00.729710Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"A Game-theoretic Framework for Privacy-preserving Federated Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.AI","cs.CR","cs.GT"],"primary_cat":"cs.LG","authors_text":"Kai Chen, Lixin Fan, Qiang Yang, Siwei Wang, Wenjie Li, Xiaojin Zhang","submitted_at":"2023-04-11T14:20:31Z","abstract_excerpt":"In federated learning, benign participants aim to optimize a global model collaboratively. However, the risk of \\textit{privacy leakage} cannot be ignored in the presence of \\textit{semi-honest} adversaries. Existing research has focused either on designing protection mechanisms or on inventing attacking mechanisms. While the battle between defenders and attackers seems never-ending, we are concerned with one critical question: is it possible to prevent potential attacks in advance? To address this, we propose the first game-theoretic framework that considers both FL defenders and attackers in"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2304.05836","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/2304.05836/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":"2304.05836","created_at":"2026-07-05T07:50:00.729769+00:00"},{"alias_kind":"arxiv_version","alias_value":"2304.05836v3","created_at":"2026-07-05T07:50:00.729769+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2304.05836","created_at":"2026-07-05T07:50:00.729769+00:00"},{"alias_kind":"pith_short_12","alias_value":"U6G6HOKTPYG2","created_at":"2026-07-05T07:50:00.729769+00:00"},{"alias_kind":"pith_short_16","alias_value":"U6G6HOKTPYG2TNNG","created_at":"2026-07-05T07:50:00.729769+00:00"},{"alias_kind":"pith_short_8","alias_value":"U6G6HOKT","created_at":"2026-07-05T07:50:00.729769+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/U6G6HOKTPYG2TNNGEY7C44NYQG","json":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG.json","graph_json":"https://pith.science/api/pith-number/U6G6HOKTPYG2TNNGEY7C44NYQG/graph.json","events_json":"https://pith.science/api/pith-number/U6G6HOKTPYG2TNNGEY7C44NYQG/events.json","paper":"https://pith.science/paper/U6G6HOKT"},"agent_actions":{"view_html":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG","download_json":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG.json","view_paper":"https://pith.science/paper/U6G6HOKT","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2304.05836&json=true","fetch_graph":"https://pith.science/api/pith-number/U6G6HOKTPYG2TNNGEY7C44NYQG/graph.json","fetch_events":"https://pith.science/api/pith-number/U6G6HOKTPYG2TNNGEY7C44NYQG/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG/action/timestamp_anchor","attest_storage":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG/action/storage_attestation","attest_author":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG/action/author_attestation","sign_citation":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG/action/citation_signature","submit_replication":"https://pith.science/pith/U6G6HOKTPYG2TNNGEY7C44NYQG/action/replication_record"}},"created_at":"2026-07-05T07:50:00.729769+00:00","updated_at":"2026-07-05T07:50:00.729769+00:00"}