{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2023:CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP","short_pith_number":"pith:CZ7Y4Q4M","schema_version":"1.0","canonical_sha256":"167f8e438c8d079085fec9471882ddb3c363ffb6ac611d04db0a3877da11f6dc","source":{"kind":"arxiv","id":"2303.18086","version":3},"attestation_state":"computed","paper":{"title":"Differentially Private Stream Processing at Scale","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.CR","authors_text":"Abhradeep Thakurta, Bing Zhang, Eidan Cohen, Himani Apte, Jodi Spacek, Peter Kairouz, Thomas Steinke, Vadym Doroshenko, Ziyin Ma","submitted_at":"2023-03-31T14:23:48Z","abstract_excerpt":"We design, to the best of our knowledge, the first differentially private (DP) stream aggregation processing system at scale. Our system -- Differential Privacy SQL Pipelines (DP-SQLP) -- is built using a streaming framework similar to Spark streaming, and is built on top of the Spanner database and the F1 query engine from Google.\n  Towards designing DP-SQLP we make both algorithmic and systemic advances, namely, we (i) design a novel (user-level) DP key selection algorithm that can operate on an unbounded set of possible keys, and can scale to one billion keys that users have contributed, (i"},"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":"2303.18086","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-03-31T14:23:48Z","cross_cats_sorted":["cs.DB"],"title_canon_sha256":"fb9972b2664034217c09ea1b89b007819ef0cac9303e95b857b55cdfc3e177f8","abstract_canon_sha256":"7d6df2c71b47e4ca6dacfd8dfde52047d84206808dbb71f29e4b305523d88cd1"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T08:43:21.739421Z","signature_b64":"x7lwgK0DJgNvCk2oRWvgI5leFRylqZbRgn/D78XKeOH/cAPXyFqGn2aQypG8//m0nc7keFN/xA7+E2GyI02oBA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"167f8e438c8d079085fec9471882ddb3c363ffb6ac611d04db0a3877da11f6dc","last_reissued_at":"2026-07-05T08:43:21.738883Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T08:43:21.738883Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Differentially Private Stream Processing at Scale","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.DB"],"primary_cat":"cs.CR","authors_text":"Abhradeep Thakurta, Bing Zhang, Eidan Cohen, Himani Apte, Jodi Spacek, Peter Kairouz, Thomas Steinke, Vadym Doroshenko, Ziyin Ma","submitted_at":"2023-03-31T14:23:48Z","abstract_excerpt":"We design, to the best of our knowledge, the first differentially private (DP) stream aggregation processing system at scale. Our system -- Differential Privacy SQL Pipelines (DP-SQLP) -- is built using a streaming framework similar to Spark streaming, and is built on top of the Spanner database and the F1 query engine from Google.\n  Towards designing DP-SQLP we make both algorithmic and systemic advances, namely, we (i) design a novel (user-level) DP key selection algorithm that can operate on an unbounded set of possible keys, and can scale to one billion keys that users have contributed, (i"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2303.18086","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/2303.18086/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":"2303.18086","created_at":"2026-07-05T08:43:21.738933+00:00"},{"alias_kind":"arxiv_version","alias_value":"2303.18086v3","created_at":"2026-07-05T08:43:21.738933+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2303.18086","created_at":"2026-07-05T08:43:21.738933+00:00"},{"alias_kind":"pith_short_12","alias_value":"CZ7Y4Q4MRUDZ","created_at":"2026-07-05T08:43:21.738933+00:00"},{"alias_kind":"pith_short_16","alias_value":"CZ7Y4Q4MRUDZBBP6","created_at":"2026-07-05T08:43:21.738933+00:00"},{"alias_kind":"pith_short_8","alias_value":"CZ7Y4Q4M","created_at":"2026-07-05T08:43:21.738933+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":2,"internal_anchor_count":0,"sample":[{"citing_arxiv_id":"2605.21378","citing_title":"Auditing Apple's DifferentialPrivacy.framework: Implementation Bugs, Misconfigurations, and Practical Risks","ref_index":3,"is_internal_anchor":false},{"citing_arxiv_id":"2605.21378","citing_title":"Auditing Apple's DifferentialPrivacy.framework: Implementation Bugs, Misconfigurations, and Practical Risks","ref_index":3,"is_internal_anchor":false}]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP","json":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP.json","graph_json":"https://pith.science/api/pith-number/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/graph.json","events_json":"https://pith.science/api/pith-number/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/events.json","paper":"https://pith.science/paper/CZ7Y4Q4M"},"agent_actions":{"view_html":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP","download_json":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP.json","view_paper":"https://pith.science/paper/CZ7Y4Q4M","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2303.18086&json=true","fetch_graph":"https://pith.science/api/pith-number/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/graph.json","fetch_events":"https://pith.science/api/pith-number/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/action/storage_attestation","attest_author":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/action/author_attestation","sign_citation":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/action/citation_signature","submit_replication":"https://pith.science/pith/CZ7Y4Q4MRUDZBBP6ZFDRRAW5WP/action/replication_record"}},"created_at":"2026-07-05T08:43:21.738933+00:00","updated_at":"2026-07-05T08:43:21.738933+00:00"}