{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:YPSNFGJ7VWEEOWO2Z5S5FKBEUB","short_pith_number":"pith:YPSNFGJ7","canonical_record":{"source":{"id":"2507.12098","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-07-16T10:07:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"15b3782b7e6edf2c1bed8500f76c6ad2c5edd3b91e879cf7c3d432673c756d9d","abstract_canon_sha256":"66e08eeda5c9676ef4e014b0110e7780e3f8ff6f99e0052533d797d189e66e62"},"schema_version":"1.0"},"canonical_sha256":"c3e4d2993fad884759dacf65d2a824a06c21005acf0c296b4df8a0029353c504","source":{"kind":"arxiv","id":"2507.12098","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.12098","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"arxiv_version","alias_value":"2507.12098v1","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.12098","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_12","alias_value":"YPSNFGJ7VWEE","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_16","alias_value":"YPSNFGJ7VWEEOWO2","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_8","alias_value":"YPSNFGJ7","created_at":"2026-07-05T11:38:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:YPSNFGJ7VWEEOWO2Z5S5FKBEUB","target":"record","payload":{"canonical_record":{"source":{"id":"2507.12098","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-07-16T10:07:19Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"15b3782b7e6edf2c1bed8500f76c6ad2c5edd3b91e879cf7c3d432673c756d9d","abstract_canon_sha256":"66e08eeda5c9676ef4e014b0110e7780e3f8ff6f99e0052533d797d189e66e62"},"schema_version":"1.0"},"canonical_sha256":"c3e4d2993fad884759dacf65d2a824a06c21005acf0c296b4df8a0029353c504","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T11:38:14.505269Z","signature_b64":"0x5rg5l/p0wzwFknGoKqMkAgouD2dtudUWhIvjZfi3pZiwwsala76cIJ/wGStEKCtuFlhkkcwxgwZWsNdNxZDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c3e4d2993fad884759dacf65d2a824a06c21005acf0c296b4df8a0029353c504","last_reissued_at":"2026-07-05T11:38:14.504768Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T11:38:14.504768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2507.12098","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":"2026-07-05T11:38:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"CY4u78KLB9iQKTKuiFWziVM/gnWCbgdEfu607YeS+CE6F8ctOC+u6KoJZtIFok3NhocyQwxbDKp4znr6uuxQBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:57:34.187465Z"},"content_sha256":"6b5b3e4210cc8e32a5f3a84f0f569fcd17b586a3385e9347fa5f7ac415b1ace0","schema_version":"1.0","event_id":"sha256:6b5b3e4210cc8e32a5f3a84f0f569fcd17b586a3385e9347fa5f7ac415b1ace0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:YPSNFGJ7VWEEOWO2Z5S5FKBEUB","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Xiang Li, Yifan Lin, Yuanzhe Zhang","submitted_at":"2025-07-16T10:07:19Z","abstract_excerpt":"To mitigate privacy leakage and performance issues in personalized advertising, this paper proposes a framework that integrates federated learning and differential privacy. The system combines distributed feature extraction, dynamic privacy budget allocation, and robust model aggregation to balance model accuracy, communication overhead, and privacy protection. Multi-party secure computing and anomaly detection mechanisms further enhance system resilience against malicious attacks. Experimental results demonstrate that the framework achieves dual optimization of recommendation accuracy and sys"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.12098","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/2507.12098/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":"2026-07-05T11:38:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Ea2e5ofaFhLzCNO5eNvrwNkZq3BQgAkvq4tX2/rs/9vJp+3RDlXXTaMZg4J6HxBZ23YUxN50kL3qFFB/jPXYDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T06:57:34.188355Z"},"content_sha256":"f002339b00718e0ede479038bf2ad74b2b2ececb642dbf6c189c5670cd52ad8b","schema_version":"1.0","event_id":"sha256:f002339b00718e0ede479038bf2ad74b2b2ececb642dbf6c189c5670cd52ad8b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/bundle.json","state_url":"https://pith.science/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/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":"2026-08-07T06:57:34Z","links":{"resolver":"https://pith.science/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB","bundle":"https://pith.science/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/bundle.json","state":"https://pith.science/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YPSNFGJ7VWEEOWO2Z5S5FKBEUB/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:YPSNFGJ7VWEEOWO2Z5S5FKBEUB","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":"66e08eeda5c9676ef4e014b0110e7780e3f8ff6f99e0052533d797d189e66e62","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-07-16T10:07:19Z","title_canon_sha256":"15b3782b7e6edf2c1bed8500f76c6ad2c5edd3b91e879cf7c3d432673c756d9d"},"schema_version":"1.0","source":{"id":"2507.12098","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2507.12098","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"arxiv_version","alias_value":"2507.12098v1","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2507.12098","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_12","alias_value":"YPSNFGJ7VWEE","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_16","alias_value":"YPSNFGJ7VWEEOWO2","created_at":"2026-07-05T11:38:14Z"},{"alias_kind":"pith_short_8","alias_value":"YPSNFGJ7","created_at":"2026-07-05T11:38:14Z"}],"graph_snapshots":[{"event_id":"sha256:f002339b00718e0ede479038bf2ad74b2b2ececb642dbf6c189c5670cd52ad8b","target":"graph","created_at":"2026-07-05T11:38:14Z","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/2507.12098/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To mitigate privacy leakage and performance issues in personalized advertising, this paper proposes a framework that integrates federated learning and differential privacy. The system combines distributed feature extraction, dynamic privacy budget allocation, and robust model aggregation to balance model accuracy, communication overhead, and privacy protection. Multi-party secure computing and anomaly detection mechanisms further enhance system resilience against malicious attacks. Experimental results demonstrate that the framework achieves dual optimization of recommendation accuracy and sys","authors_text":"Xiang Li, Yifan Lin, Yuanzhe Zhang","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-07-16T10:07:19Z","title":"A Privacy-Preserving Framework for Advertising Personalization Incorporating Federated Learning and Differential Privacy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2507.12098","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":"sha256:6b5b3e4210cc8e32a5f3a84f0f569fcd17b586a3385e9347fa5f7ac415b1ace0","target":"record","created_at":"2026-07-05T11:38:14Z","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":"66e08eeda5c9676ef4e014b0110e7780e3f8ff6f99e0052533d797d189e66e62","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2025-07-16T10:07:19Z","title_canon_sha256":"15b3782b7e6edf2c1bed8500f76c6ad2c5edd3b91e879cf7c3d432673c756d9d"},"schema_version":"1.0","source":{"id":"2507.12098","kind":"arxiv","version":1}},"canonical_sha256":"c3e4d2993fad884759dacf65d2a824a06c21005acf0c296b4df8a0029353c504","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c3e4d2993fad884759dacf65d2a824a06c21005acf0c296b4df8a0029353c504","first_computed_at":"2026-07-05T11:38:14.504768Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T11:38:14.504768Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0x5rg5l/p0wzwFknGoKqMkAgouD2dtudUWhIvjZfi3pZiwwsala76cIJ/wGStEKCtuFlhkkcwxgwZWsNdNxZDg==","signature_status":"signed_v1","signed_at":"2026-07-05T11:38:14.505269Z","signed_message":"canonical_sha256_bytes"},"source_id":"2507.12098","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b5b3e4210cc8e32a5f3a84f0f569fcd17b586a3385e9347fa5f7ac415b1ace0","sha256:f002339b00718e0ede479038bf2ad74b2b2ececb642dbf6c189c5670cd52ad8b"],"state_sha256":"93d32d1ad1a840beae63ade7f11ca07d9fefe751d80cfc74319835b237e41792"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZsYfUf9NPhvfhGBmXT0MhDh6UypH732SOv2lHxfKxRhSSjhazMhR3pHDTW8OfMDUBPthvqZKEg1WnkUzfJOvAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T06:57:34.194859Z","bundle_sha256":"aa101e6aa704fad88fe009f11b8b3e37c0325eda3a0ffa7d9df6ed1b154dfc09"}}