{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2018:WL3THSAHK7HLTNJH6FFBG6UXTP","short_pith_number":"pith:WL3THSAH","schema_version":"1.0","canonical_sha256":"b2f733c80757ceb9b527f14a137a979bd72e9d630a7ee296a3a2e7d5e36b1292","source":{"kind":"arxiv","id":"1809.08634","version":1},"attestation_state":"computed","paper":{"title":"Towards Differential Privacy for Symbolic Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.CR","authors_text":"Austin Jones, Kevin Leahy, Matthew Hale","submitted_at":"2018-09-23T17:11:24Z","abstract_excerpt":"In this paper, we develop a privacy implementation for symbolic control systems. Such systems generate sequences of non-numerical data, and these sequences can be represented by words or strings over a finite alphabet. This work uses the framework of differential privacy, which is a statistical notion of privacy that makes it unlikely that privatized data will reveal anything meaningful about underlying sensitive data. To bring differential privacy to symbolic control systems, we develop an exponential mechanism that approximates a sensitive word using a randomly chosen word that is likely to "},"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":"1809.08634","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2018-09-23T17:11:24Z","cross_cats_sorted":["math.OC"],"title_canon_sha256":"a39554f7f1ef757a265b98983117cf6622e1a0bddd5c37cdba649832e5f889ab","abstract_canon_sha256":"7f052fbfd3d76918218d4742f7bbfa3e8da905929ce107f4b06ba89ec5c9c4a4"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:05:03.942782Z","signature_b64":"x+jvllMIb6mtE5oZ1JFw3llMhGS57yC5BQbU9OXXT2lvWVmLl41aAw72vcSHPtLD4GxYW5fH03JqULNWEIRODw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"b2f733c80757ceb9b527f14a137a979bd72e9d630a7ee296a3a2e7d5e36b1292","last_reissued_at":"2026-05-18T00:05:03.942228Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:05:03.942228Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards Differential Privacy for Symbolic Systems","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.OC"],"primary_cat":"cs.CR","authors_text":"Austin Jones, Kevin Leahy, Matthew Hale","submitted_at":"2018-09-23T17:11:24Z","abstract_excerpt":"In this paper, we develop a privacy implementation for symbolic control systems. Such systems generate sequences of non-numerical data, and these sequences can be represented by words or strings over a finite alphabet. This work uses the framework of differential privacy, which is a statistical notion of privacy that makes it unlikely that privatized data will reveal anything meaningful about underlying sensitive data. To bring differential privacy to symbolic control systems, we develop an exponential mechanism that approximates a sensitive word using a randomly chosen word that is likely to "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1809.08634","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":""},"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":"1809.08634","created_at":"2026-05-18T00:05:03.942324+00:00"},{"alias_kind":"arxiv_version","alias_value":"1809.08634v1","created_at":"2026-05-18T00:05:03.942324+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1809.08634","created_at":"2026-05-18T00:05:03.942324+00:00"},{"alias_kind":"pith_short_12","alias_value":"WL3THSAHK7HL","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_16","alias_value":"WL3THSAHK7HLTNJH","created_at":"2026-05-18T12:33:01.666342+00:00"},{"alias_kind":"pith_short_8","alias_value":"WL3THSAH","created_at":"2026-05-18T12:33:01.666342+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/WL3THSAHK7HLTNJH6FFBG6UXTP","json":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP.json","graph_json":"https://pith.science/api/pith-number/WL3THSAHK7HLTNJH6FFBG6UXTP/graph.json","events_json":"https://pith.science/api/pith-number/WL3THSAHK7HLTNJH6FFBG6UXTP/events.json","paper":"https://pith.science/paper/WL3THSAH"},"agent_actions":{"view_html":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP","download_json":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP.json","view_paper":"https://pith.science/paper/WL3THSAH","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1809.08634&json=true","fetch_graph":"https://pith.science/api/pith-number/WL3THSAHK7HLTNJH6FFBG6UXTP/graph.json","fetch_events":"https://pith.science/api/pith-number/WL3THSAHK7HLTNJH6FFBG6UXTP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP/action/storage_attestation","attest_author":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP/action/author_attestation","sign_citation":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP/action/citation_signature","submit_replication":"https://pith.science/pith/WL3THSAHK7HLTNJH6FFBG6UXTP/action/replication_record"}},"created_at":"2026-05-18T00:05:03.942324+00:00","updated_at":"2026-05-18T00:05:03.942324+00:00"}