{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:RX4O5DK2JZJH2VRSQ26PS4L6VQ","short_pith_number":"pith:RX4O5DK2","schema_version":"1.0","canonical_sha256":"8df8ee8d5a4e527d563286bcf9717eac17898a8fa81c6210ea45ba1558ed07c3","source":{"kind":"arxiv","id":"1908.06972","version":2},"attestation_state":"computed","paper":{"title":"PrivFT: Private and Fast Text Classification with Homomorphic Encryption","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Ahmad Al Badawi, Chan Fook Mun, Khin Mi Mi Aung, Kim Laine, Luong Hoang","submitted_at":"2019-08-19T03:44:57Z","abstract_excerpt":"The need for privacy-preserving analytics is higher than ever due to the severity of privacy risks and to comply with new privacy regulations leading to an amplified interest in privacy-preserving techniques that try to balance between privacy and utility. In this work, we present an efficient method for Text Classification while preserving the privacy of the content using Fully Homomorphic Encryption (FHE). Our system (named \\textbf{Priv}ate \\textbf{F}ast \\textbf{T}ext (PrivFT)) performs two tasks: 1) making inference of encrypted user inputs using a plaintext model and 2) training an effecti"},"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":"1908.06972","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-08-19T03:44:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4c9ba7f162d2b4a91233bdff5f23c1c5a507b41e8d60519c8fd71140adb8fc26","abstract_canon_sha256":"2991772e23b395f92baeffc3baee428969d0153ac568ab03830efb57fa248a6b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:04:03.964178Z","signature_b64":"Qr2wzmJDs08A2M9Ml7Fp0e8BwXb57Oug9p7BZ7n1uKhhO8XoZJlm84EKBvYwxEnEd/KJI+MqA9AjcM1dc3IeAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8df8ee8d5a4e527d563286bcf9717eac17898a8fa81c6210ea45ba1558ed07c3","last_reissued_at":"2026-07-05T02:04:03.963787Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:04:03.963787Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"PrivFT: Private and Fast Text Classification with Homomorphic Encryption","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Ahmad Al Badawi, Chan Fook Mun, Khin Mi Mi Aung, Kim Laine, Luong Hoang","submitted_at":"2019-08-19T03:44:57Z","abstract_excerpt":"The need for privacy-preserving analytics is higher than ever due to the severity of privacy risks and to comply with new privacy regulations leading to an amplified interest in privacy-preserving techniques that try to balance between privacy and utility. In this work, we present an efficient method for Text Classification while preserving the privacy of the content using Fully Homomorphic Encryption (FHE). Our system (named \\textbf{Priv}ate \\textbf{F}ast \\textbf{T}ext (PrivFT)) performs two tasks: 1) making inference of encrypted user inputs using a plaintext model and 2) training an effecti"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.06972","kind":"arxiv","version":2},"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/1908.06972/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":"1908.06972","created_at":"2026-07-05T02:04:03.963842+00:00"},{"alias_kind":"arxiv_version","alias_value":"1908.06972v2","created_at":"2026-07-05T02:04:03.963842+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.06972","created_at":"2026-07-05T02:04:03.963842+00:00"},{"alias_kind":"pith_short_12","alias_value":"RX4O5DK2JZJH","created_at":"2026-07-05T02:04:03.963842+00:00"},{"alias_kind":"pith_short_16","alias_value":"RX4O5DK2JZJH2VRS","created_at":"2026-07-05T02:04:03.963842+00:00"},{"alias_kind":"pith_short_8","alias_value":"RX4O5DK2","created_at":"2026-07-05T02:04:03.963842+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/RX4O5DK2JZJH2VRSQ26PS4L6VQ","json":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ.json","graph_json":"https://pith.science/api/pith-number/RX4O5DK2JZJH2VRSQ26PS4L6VQ/graph.json","events_json":"https://pith.science/api/pith-number/RX4O5DK2JZJH2VRSQ26PS4L6VQ/events.json","paper":"https://pith.science/paper/RX4O5DK2"},"agent_actions":{"view_html":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ","download_json":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ.json","view_paper":"https://pith.science/paper/RX4O5DK2","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1908.06972&json=true","fetch_graph":"https://pith.science/api/pith-number/RX4O5DK2JZJH2VRSQ26PS4L6VQ/graph.json","fetch_events":"https://pith.science/api/pith-number/RX4O5DK2JZJH2VRSQ26PS4L6VQ/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ/action/timestamp_anchor","attest_storage":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ/action/storage_attestation","attest_author":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ/action/author_attestation","sign_citation":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ/action/citation_signature","submit_replication":"https://pith.science/pith/RX4O5DK2JZJH2VRSQ26PS4L6VQ/action/replication_record"}},"created_at":"2026-07-05T02:04:03.963842+00:00","updated_at":"2026-07-05T02:04:03.963842+00:00"}