{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:JKCGUAHB2NZHU6LXQSW2BF32NB","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":"0e12964c6364a148e9623835ad8366af6d7fed335c44d638adee9370a66ca376","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-08-04T14:30:55Z","title_canon_sha256":"b8732fc47d13ac93f527a81390193b700ee655d568e76d38f27c9b3f6f7985cc"},"schema_version":"1.0","source":{"id":"2608.03737","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2608.03737","created_at":"2026-08-05T01:36:59Z"},{"alias_kind":"arxiv_version","alias_value":"2608.03737v1","created_at":"2026-08-05T01:36:59Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2608.03737","created_at":"2026-08-05T01:36:59Z"},{"alias_kind":"pith_short_12","alias_value":"JKCGUAHB2NZH","created_at":"2026-08-05T01:36:59Z"},{"alias_kind":"pith_short_16","alias_value":"JKCGUAHB2NZHU6LX","created_at":"2026-08-05T01:36:59Z"},{"alias_kind":"pith_short_8","alias_value":"JKCGUAHB","created_at":"2026-08-05T01:36:59Z"}],"graph_snapshots":[{"event_id":"sha256:f9e26d3aeedf0373dbf94e1b9b09e8a34784e2e508773065488f824743a8d216","target":"graph","created_at":"2026-08-05T01:36:59Z","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/2608.03737/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Collecting multidimensional user data is essential for extracting rich insights across various applications. Local Differential Privacy (LDP) has emerged as a de facto standard for mitigating privacy risks in such scenarios. A key challenge in privacy-preserving multidimensional data collection lies in inter-attribute dependencies, as they can inadvertently reveal correlated information and increase privacy vulnerabilities. Therefore, accurately measuring correlation-induced privacy leakage (CPL) is essential for privacy analysis and privacy-utility trade-off. However, existing CPL analysis so","authors_text":"Kanchana Thilakarathna, Ming Ding, Sandaru Jayawardana, Sennur Ulukus","cross_cats":["cs.IT","math.IT"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-08-04T14:30:55Z","title":"Dependency Triad: A Metric to Quantify the Dependencies Between Attributes for Local Differential Privacy"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2608.03737","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":"sha256:08f3388324ea281fe21a35544481db68126778527f266815faa1c3cbc47691ec","target":"record","created_at":"2026-08-05T01:36:59Z","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":"0e12964c6364a148e9623835ad8366af6d7fed335c44d638adee9370a66ca376","cross_cats_sorted":["cs.IT","math.IT"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2026-08-04T14:30:55Z","title_canon_sha256":"b8732fc47d13ac93f527a81390193b700ee655d568e76d38f27c9b3f6f7985cc"},"schema_version":"1.0","source":{"id":"2608.03737","kind":"arxiv","version":1}},"canonical_sha256":"4a846a00e1d3727a797784ada0977a6846a2fb6b1b27ce64d0f25eafbf55e51a","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"4a846a00e1d3727a797784ada0977a6846a2fb6b1b27ce64d0f25eafbf55e51a","first_computed_at":"2026-08-05T01:36:59.411634Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-08-05T01:36:59.411634Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"tFT86lxyYDmUwC71BlO/pfuhIXgO01dROjA5dotNk2tZ4tnoqkE4+4NyBk0BkGlp9AICTBcEh61A3KbgCu9tDg==","signature_status":"signed_v1","signed_at":"2026-08-05T01:36:59.413045Z","signed_message":"canonical_sha256_bytes"},"source_id":"2608.03737","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:08f3388324ea281fe21a35544481db68126778527f266815faa1c3cbc47691ec","sha256:f9e26d3aeedf0373dbf94e1b9b09e8a34784e2e508773065488f824743a8d216"],"state_sha256":"9fbb62f606af8b3b2a5f413e574e3e7fc8279d4a4e0341382b6ef67f49b9355a"}