{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:M6GG7MI7TDBLRN3NWP7LWJZZE4","short_pith_number":"pith:M6GG7MI7","canonical_record":{"source":{"id":"2006.05535","kind":"arxiv","version":9},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-09T22:36:06Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"05db35569a73d966a717c6a1224b2bbf70463e870cd19bb73beab9ee89ac478b","abstract_canon_sha256":"962973fb7a776b2542de30cae635777409199cd45718a8f123a2a4f73f7a0972"},"schema_version":"1.0"},"canonical_sha256":"678c6fb11f98c2b8b76db3febb273927257e84b23aaf2c53db5dab91bfb49e90","source":{"kind":"arxiv","id":"2006.05535","version":9},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.05535","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"arxiv_version","alias_value":"2006.05535v9","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.05535","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_12","alias_value":"M6GG7MI7TDBL","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_16","alias_value":"M6GG7MI7TDBLRN3N","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_8","alias_value":"M6GG7MI7","created_at":"2026-07-05T02:55:51Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:M6GG7MI7TDBLRN3NWP7LWJZZE4","target":"record","payload":{"canonical_record":{"source":{"id":"2006.05535","kind":"arxiv","version":9},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-09T22:36:06Z","cross_cats_sorted":["cs.CR","stat.ML"],"title_canon_sha256":"05db35569a73d966a717c6a1224b2bbf70463e870cd19bb73beab9ee89ac478b","abstract_canon_sha256":"962973fb7a776b2542de30cae635777409199cd45718a8f123a2a4f73f7a0972"},"schema_version":"1.0"},"canonical_sha256":"678c6fb11f98c2b8b76db3febb273927257e84b23aaf2c53db5dab91bfb49e90","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:55:51.918435Z","signature_b64":"c2FyMUVLQcrPAWocMH0QUmnSbG5kP49Ww7NXr2DCZlt4lAAHYltmCaLCoaliEjw/87tQqYy4KB5sI94Qq4w/BA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"678c6fb11f98c2b8b76db3febb273927257e84b23aaf2c53db5dab91bfb49e90","last_reissued_at":"2026-07-05T02:55:51.918046Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:55:51.918046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2006.05535","source_version":9,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:55:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"szEkpSARbtSvtxDshea61KBTOIg+RvLCJYIu9MKaX9SySCsZ0P3l4Y+ko+w2IA6ns+h+bo+HI8+jFqM3e5/0BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:58:51.938790Z"},"content_sha256":"5f04c7b096ec6ababed183baebdc7cb9b81a5d1182b78f728449b2e07ca1e181","schema_version":"1.0","event_id":"sha256:5f04c7b096ec6ababed183baebdc7cb9b81a5d1182b78f728449b2e07ca1e181"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:M6GG7MI7TDBLRN3NWP7LWJZZE4","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Locally Private Graph Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","stat.ML"],"primary_cat":"cs.LG","authors_text":"Daniel Gatica-Perez, Sina Sajadmanesh","submitted_at":"2020-06-09T22:36:06Z","abstract_excerpt":"Graph Neural Networks (GNNs) have demonstrated superior performance in learning node representations for various graph inference tasks. However, learning over graph data can raise privacy concerns when nodes represent people or human-related variables that involve sensitive or personal information. While numerous techniques have been proposed for privacy-preserving deep learning over non-relational data, there is less work addressing the privacy issues pertained to applying deep learning algorithms on graphs. In this paper, we study the problem of node data privacy, where graph nodes have pote"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.05535","kind":"arxiv","version":9},"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/2006.05535/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T02:55:51Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XJaMS9ugdyXCzh+CgeoIL7/t0LfbrB2ec0K7swkvw+LacccP8Nj/cjRlAq7NNyi6u5m9QYKXmFxDKzzlA8apDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T09:58:51.939337Z"},"content_sha256":"628e6434cd88ab672bd45da2f68e63f642ea9a6a5e354a2afd50239049d7f76c","schema_version":"1.0","event_id":"sha256:628e6434cd88ab672bd45da2f68e63f642ea9a6a5e354a2afd50239049d7f76c"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/bundle.json","state_url":"https://pith.science/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-10T09:58:51Z","links":{"resolver":"https://pith.science/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4","bundle":"https://pith.science/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/bundle.json","state":"https://pith.science/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/state.json","well_known_bundle":"https://pith.science/.well-known/pith/M6GG7MI7TDBLRN3NWP7LWJZZE4/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:M6GG7MI7TDBLRN3NWP7LWJZZE4","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":"962973fb7a776b2542de30cae635777409199cd45718a8f123a2a4f73f7a0972","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-09T22:36:06Z","title_canon_sha256":"05db35569a73d966a717c6a1224b2bbf70463e870cd19bb73beab9ee89ac478b"},"schema_version":"1.0","source":{"id":"2006.05535","kind":"arxiv","version":9}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2006.05535","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"arxiv_version","alias_value":"2006.05535v9","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2006.05535","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_12","alias_value":"M6GG7MI7TDBL","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_16","alias_value":"M6GG7MI7TDBLRN3N","created_at":"2026-07-05T02:55:51Z"},{"alias_kind":"pith_short_8","alias_value":"M6GG7MI7","created_at":"2026-07-05T02:55:51Z"}],"graph_snapshots":[{"event_id":"sha256:628e6434cd88ab672bd45da2f68e63f642ea9a6a5e354a2afd50239049d7f76c","target":"graph","created_at":"2026-07-05T02:55:51Z","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/2006.05535/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) have demonstrated superior performance in learning node representations for various graph inference tasks. However, learning over graph data can raise privacy concerns when nodes represent people or human-related variables that involve sensitive or personal information. While numerous techniques have been proposed for privacy-preserving deep learning over non-relational data, there is less work addressing the privacy issues pertained to applying deep learning algorithms on graphs. In this paper, we study the problem of node data privacy, where graph nodes have pote","authors_text":"Daniel Gatica-Perez, Sina Sajadmanesh","cross_cats":["cs.CR","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-09T22:36:06Z","title":"Locally Private Graph Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2006.05535","kind":"arxiv","version":9},"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":"sha256:5f04c7b096ec6ababed183baebdc7cb9b81a5d1182b78f728449b2e07ca1e181","target":"record","created_at":"2026-07-05T02:55:51Z","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":"962973fb7a776b2542de30cae635777409199cd45718a8f123a2a4f73f7a0972","cross_cats_sorted":["cs.CR","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2020-06-09T22:36:06Z","title_canon_sha256":"05db35569a73d966a717c6a1224b2bbf70463e870cd19bb73beab9ee89ac478b"},"schema_version":"1.0","source":{"id":"2006.05535","kind":"arxiv","version":9}},"canonical_sha256":"678c6fb11f98c2b8b76db3febb273927257e84b23aaf2c53db5dab91bfb49e90","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"678c6fb11f98c2b8b76db3febb273927257e84b23aaf2c53db5dab91bfb49e90","first_computed_at":"2026-07-05T02:55:51.918046Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:55:51.918046Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"c2FyMUVLQcrPAWocMH0QUmnSbG5kP49Ww7NXr2DCZlt4lAAHYltmCaLCoaliEjw/87tQqYy4KB5sI94Qq4w/BA==","signature_status":"signed_v1","signed_at":"2026-07-05T02:55:51.918435Z","signed_message":"canonical_sha256_bytes"},"source_id":"2006.05535","source_kind":"arxiv","source_version":9}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:5f04c7b096ec6ababed183baebdc7cb9b81a5d1182b78f728449b2e07ca1e181","sha256:628e6434cd88ab672bd45da2f68e63f642ea9a6a5e354a2afd50239049d7f76c"],"state_sha256":"c1cb241f1534e3c3b76b7ebf6c24c1f926a75cb6ea62a9c15e06d51d132c9922"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MVP/z1nzGeViU88oeLHs+VzvWQIiG7n5+XdITh5gxy6ZsHhFW49VxP1OJ3sXF7fRLRUL9sWj03xi6Rn4bjHdDQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T09:58:51.943689Z","bundle_sha256":"d908ac89eabece735d4f1957b2d27094242dcf568e5bdc354feee3eb80258db9"}}