{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:MWDKT44RRR6G6M75L4CJBHLZFG","short_pith_number":"pith:MWDKT44R","canonical_record":{"source":{"id":"2111.15521","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T16:18:53Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"ec6a96884e3de4a36b2f7b3206eddee9bf07732e194bbd5a6bab8ad915d2794c","abstract_canon_sha256":"7243f6a839e8fcf63d96eb5e89c421f5890b57ec49ae98065d3dcae8cdac33fb"},"schema_version":"1.0"},"canonical_sha256":"6586a9f3918c7c6f33fd5f04909d79299a0722fd10e78af9b7753dac781cc43f","source":{"kind":"arxiv","id":"2111.15521","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.15521","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"arxiv_version","alias_value":"2111.15521v3","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.15521","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_12","alias_value":"MWDKT44RRR6G","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_16","alias_value":"MWDKT44RRR6G6M75","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_8","alias_value":"MWDKT44R","created_at":"2026-07-05T04:51:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:MWDKT44RRR6G6M75L4CJBHLZFG","target":"record","payload":{"canonical_record":{"source":{"id":"2111.15521","kind":"arxiv","version":3},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T16:18:53Z","cross_cats_sorted":["cs.CR"],"title_canon_sha256":"ec6a96884e3de4a36b2f7b3206eddee9bf07732e194bbd5a6bab8ad915d2794c","abstract_canon_sha256":"7243f6a839e8fcf63d96eb5e89c421f5890b57ec49ae98065d3dcae8cdac33fb"},"schema_version":"1.0"},"canonical_sha256":"6586a9f3918c7c6f33fd5f04909d79299a0722fd10e78af9b7753dac781cc43f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:51:53.748393Z","signature_b64":"9IQCBokTM2u7WXUM/IEwqsNiwINqt4PSbSTpuw2n7d3FzpW3/h0EEMfJtrd4pk1TisPT/68ZU2n/XZS84YksBg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"6586a9f3918c7c6f33fd5f04909d79299a0722fd10e78af9b7753dac781cc43f","last_reissued_at":"2026-07-05T04:51:53.747920Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:51:53.747920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2111.15521","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T04:51:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"osoxUJzFFuEJRmfmWXaKi64IQGICsRhzVFAJ7lHYV5mB8swD8yiEdKTWrz8PXZx07ZVQHGqOKz+m4BHbciFPBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:42:15.462054Z"},"content_sha256":"8e5a36087b9b37d5638431eff8e86357ee9cc224609105d13b7ec9fe9b04ba4f","schema_version":"1.0","event_id":"sha256:8e5a36087b9b37d5638431eff8e86357ee9cc224609105d13b7ec9fe9b04ba4f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:MWDKT44RRR6G6M75L4CJBHLZFG","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Node-Level Differentially Private Graph Neural Networks","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","headline":"","cross_cats":["cs.CR"],"primary_cat":"cs.LG","authors_text":"Abhradeep Guha Thakurta, Aditya Sinha, Ameya Daigavane, Gagan Madan, Gaurav Aggarwal, Prateek Jain","submitted_at":"2021-11-23T16:18:53Z","abstract_excerpt":"Graph Neural Networks (GNNs) are a popular technique for modelling graph-structured data and computing node-level representations via aggregation of information from the neighborhood of each node. However, this aggregation implies an increased risk of revealing sensitive information, as a node can participate in the inference for multiple nodes. This implies that standard privacy-preserving machine learning techniques, such as differentially private stochastic gradient descent (DP-SGD) - which are designed for situations where each data point participates in the inference for one point only - "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.15521","kind":"arxiv","version":3},"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/2111.15521/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":"2026-07-05T04:51:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"achch5kq6s3xxP/WV6AxBi7ODKuFmRn1FjdRRZc6Wc2uH8l3KNS3PLDj9r3okPwP8Y7zXSH0xhwYtxvUB2XsAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-04T13:42:15.462962Z"},"content_sha256":"5645baccbd03737d918dcf485b12347b281acdb30856d0a7149958020856bb39","schema_version":"1.0","event_id":"sha256:5645baccbd03737d918dcf485b12347b281acdb30856d0a7149958020856bb39"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/MWDKT44RRR6G6M75L4CJBHLZFG/bundle.json","state_url":"https://pith.science/pith/MWDKT44RRR6G6M75L4CJBHLZFG/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/MWDKT44RRR6G6M75L4CJBHLZFG/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":"2026-08-04T13:42:15Z","links":{"resolver":"https://pith.science/pith/MWDKT44RRR6G6M75L4CJBHLZFG","bundle":"https://pith.science/pith/MWDKT44RRR6G6M75L4CJBHLZFG/bundle.json","state":"https://pith.science/pith/MWDKT44RRR6G6M75L4CJBHLZFG/state.json","well_known_bundle":"https://pith.science/.well-known/pith/MWDKT44RRR6G6M75L4CJBHLZFG/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:MWDKT44RRR6G6M75L4CJBHLZFG","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":"7243f6a839e8fcf63d96eb5e89c421f5890b57ec49ae98065d3dcae8cdac33fb","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T16:18:53Z","title_canon_sha256":"ec6a96884e3de4a36b2f7b3206eddee9bf07732e194bbd5a6bab8ad915d2794c"},"schema_version":"1.0","source":{"id":"2111.15521","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2111.15521","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"arxiv_version","alias_value":"2111.15521v3","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2111.15521","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_12","alias_value":"MWDKT44RRR6G","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_16","alias_value":"MWDKT44RRR6G6M75","created_at":"2026-07-05T04:51:53Z"},{"alias_kind":"pith_short_8","alias_value":"MWDKT44R","created_at":"2026-07-05T04:51:53Z"}],"graph_snapshots":[{"event_id":"sha256:5645baccbd03737d918dcf485b12347b281acdb30856d0a7149958020856bb39","target":"graph","created_at":"2026-07-05T04:51:53Z","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/2111.15521/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Graph Neural Networks (GNNs) are a popular technique for modelling graph-structured data and computing node-level representations via aggregation of information from the neighborhood of each node. However, this aggregation implies an increased risk of revealing sensitive information, as a node can participate in the inference for multiple nodes. This implies that standard privacy-preserving machine learning techniques, such as differentially private stochastic gradient descent (DP-SGD) - which are designed for situations where each data point participates in the inference for one point only - ","authors_text":"Abhradeep Guha Thakurta, Aditya Sinha, Ameya Daigavane, Gagan Madan, Gaurav Aggarwal, Prateek Jain","cross_cats":["cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T16:18:53Z","title":"Node-Level Differentially Private Graph Neural Networks"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2111.15521","kind":"arxiv","version":3},"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":"sha256:8e5a36087b9b37d5638431eff8e86357ee9cc224609105d13b7ec9fe9b04ba4f","target":"record","created_at":"2026-07-05T04:51:53Z","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":"7243f6a839e8fcf63d96eb5e89c421f5890b57ec49ae98065d3dcae8cdac33fb","cross_cats_sorted":["cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-nd/4.0/","primary_cat":"cs.LG","submitted_at":"2021-11-23T16:18:53Z","title_canon_sha256":"ec6a96884e3de4a36b2f7b3206eddee9bf07732e194bbd5a6bab8ad915d2794c"},"schema_version":"1.0","source":{"id":"2111.15521","kind":"arxiv","version":3}},"canonical_sha256":"6586a9f3918c7c6f33fd5f04909d79299a0722fd10e78af9b7753dac781cc43f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"6586a9f3918c7c6f33fd5f04909d79299a0722fd10e78af9b7753dac781cc43f","first_computed_at":"2026-07-05T04:51:53.747920Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:51:53.747920Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9IQCBokTM2u7WXUM/IEwqsNiwINqt4PSbSTpuw2n7d3FzpW3/h0EEMfJtrd4pk1TisPT/68ZU2n/XZS84YksBg==","signature_status":"signed_v1","signed_at":"2026-07-05T04:51:53.748393Z","signed_message":"canonical_sha256_bytes"},"source_id":"2111.15521","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8e5a36087b9b37d5638431eff8e86357ee9cc224609105d13b7ec9fe9b04ba4f","sha256:5645baccbd03737d918dcf485b12347b281acdb30856d0a7149958020856bb39"],"state_sha256":"38d190e9ac64841c99c150d1a46e3e95c6e3dc01b4a6954f47203835a1d54d68"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"xyr/UUcqO3DqMsougxGnitmdNYxduu8HRFqMt6U058UJIRIPlvEV7UZphEB/wWva+Yk4FGEdJkGluSzGMyUiBA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-04T13:42:15.473085Z","bundle_sha256":"c4f0629148ec5c24791b66ef018be9998234b1d6d7213cb9617f6c4ce69e60a8"}}