{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:L4WOMXYBKPMSSIFHS4UOLLKWBD","short_pith_number":"pith:L4WOMXYB","schema_version":"1.0","canonical_sha256":"5f2ce65f0153d92920a79728e5ad5608ead79cc1eff87cfc68671bf7e601a50d","source":{"kind":"arxiv","id":"2509.03024","version":1},"attestation_state":"computed","paper":{"title":"Efficient Privacy-Preserving Recommendation on Sparse Data using Fully Homomorphic Encryption","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Andr\\'e Bauer, Minxuan Zhou, Moontaha Nishat Chowdhury","submitted_at":"2025-09-03T05:15:45Z","abstract_excerpt":"In today's data-driven world, recommendation systems personalize user experiences across industries but rely on sensitive data, raising privacy concerns. Fully homomorphic encryption (FHE) can secure these systems, but a significant challenge in applying FHE to recommendation systems is efficiently handling the inherently large and sparse user-item rating matrices. FHE operations are computationally intensive, and naively processing various sparse matrices in recommendation systems would be prohibitively expensive. Additionally, the communication overhead between parties remains a critical con"},"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":"2509.03024","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.CR","submitted_at":"2025-09-03T05:15:45Z","cross_cats_sorted":["cs.AI","cs.LG"],"title_canon_sha256":"aee337a2b5b2a42d9c8614e103b6af2df988ba65c397f928678c8e5dabab073d","abstract_canon_sha256":"955bb80053107f3ac1c357c77d9a6fff967918f3ba5732c656c6c159b3e0c13b"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T12:04:02.097064Z","signature_b64":"hyG8+WUV9a51D5PCBxIGUPw0yaUZR6Z1smfncx5segcyMmbqikZ6nByFPNt96KppC/dxm7ValS6F8mytt5bJCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5f2ce65f0153d92920a79728e5ad5608ead79cc1eff87cfc68671bf7e601a50d","last_reissued_at":"2026-07-05T12:04:02.096510Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T12:04:02.096510Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Efficient Privacy-Preserving Recommendation on Sparse Data using Fully Homomorphic Encryption","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.AI","cs.LG"],"primary_cat":"cs.CR","authors_text":"Andr\\'e Bauer, Minxuan Zhou, Moontaha Nishat Chowdhury","submitted_at":"2025-09-03T05:15:45Z","abstract_excerpt":"In today's data-driven world, recommendation systems personalize user experiences across industries but rely on sensitive data, raising privacy concerns. Fully homomorphic encryption (FHE) can secure these systems, but a significant challenge in applying FHE to recommendation systems is efficiently handling the inherently large and sparse user-item rating matrices. FHE operations are computationally intensive, and naively processing various sparse matrices in recommendation systems would be prohibitively expensive. Additionally, the communication overhead between parties remains a critical con"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2509.03024","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/2509.03024/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":"2509.03024","created_at":"2026-07-05T12:04:02.096571+00:00"},{"alias_kind":"arxiv_version","alias_value":"2509.03024v1","created_at":"2026-07-05T12:04:02.096571+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2509.03024","created_at":"2026-07-05T12:04:02.096571+00:00"},{"alias_kind":"pith_short_12","alias_value":"L4WOMXYBKPMS","created_at":"2026-07-05T12:04:02.096571+00:00"},{"alias_kind":"pith_short_16","alias_value":"L4WOMXYBKPMSSIFH","created_at":"2026-07-05T12:04:02.096571+00:00"},{"alias_kind":"pith_short_8","alias_value":"L4WOMXYB","created_at":"2026-07-05T12:04:02.096571+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/L4WOMXYBKPMSSIFHS4UOLLKWBD","json":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD.json","graph_json":"https://pith.science/api/pith-number/L4WOMXYBKPMSSIFHS4UOLLKWBD/graph.json","events_json":"https://pith.science/api/pith-number/L4WOMXYBKPMSSIFHS4UOLLKWBD/events.json","paper":"https://pith.science/paper/L4WOMXYB"},"agent_actions":{"view_html":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD","download_json":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD.json","view_paper":"https://pith.science/paper/L4WOMXYB","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2509.03024&json=true","fetch_graph":"https://pith.science/api/pith-number/L4WOMXYBKPMSSIFHS4UOLLKWBD/graph.json","fetch_events":"https://pith.science/api/pith-number/L4WOMXYBKPMSSIFHS4UOLLKWBD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD/action/storage_attestation","attest_author":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD/action/author_attestation","sign_citation":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD/action/citation_signature","submit_replication":"https://pith.science/pith/L4WOMXYBKPMSSIFHS4UOLLKWBD/action/replication_record"}},"created_at":"2026-07-05T12:04:02.096571+00:00","updated_at":"2026-07-05T12:04:02.096571+00:00"}