{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:7YO7KHAYTJCX66JOYLRO5X47IM","short_pith_number":"pith:7YO7KHAY","canonical_record":{"source":{"id":"2301.08778","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-01-20T19:26:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4af12f782ceed7da9c28f0302c5546127171cf0255b020e2c0aad71ed4d40221","abstract_canon_sha256":"985db96f8f2c933a4b0f5c85118a87893244fcc803a3a3585e27628b6654e305"},"schema_version":"1.0"},"canonical_sha256":"fe1df51c189a457f792ec2e2eedf9f43282b835db5c40fbae2b872cfdb6bd0b1","source":{"kind":"arxiv","id":"2301.08778","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08778","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08778v1","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08778","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_12","alias_value":"7YO7KHAYTJCX","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_16","alias_value":"7YO7KHAYTJCX66JO","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_8","alias_value":"7YO7KHAY","created_at":"2026-07-05T05:34:52Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:7YO7KHAYTJCX66JOYLRO5X47IM","target":"record","payload":{"canonical_record":{"source":{"id":"2301.08778","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-01-20T19:26:51Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"4af12f782ceed7da9c28f0302c5546127171cf0255b020e2c0aad71ed4d40221","abstract_canon_sha256":"985db96f8f2c933a4b0f5c85118a87893244fcc803a3a3585e27628b6654e305"},"schema_version":"1.0"},"canonical_sha256":"fe1df51c189a457f792ec2e2eedf9f43282b835db5c40fbae2b872cfdb6bd0b1","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:34:52.687096Z","signature_b64":"N69tK7ZtDI6i8Uo9nbmMOSZGG2bd2Z60C7xSdVA7OCNEP+SzvbxU4ZNU3f0IFnDzxgPdoBsINV7z/ZE27KPJDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"fe1df51c189a457f792ec2e2eedf9f43282b835db5c40fbae2b872cfdb6bd0b1","last_reissued_at":"2026-07-05T05:34:52.686638Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:34:52.686638Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.08778","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:34:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"DwEe1pxm0Q9jEFUDFIkKPnEEiXt5eNgilmZ+zknnYn8f2nNE6HPHHSq83addd2lovRiPnQkd/92iGlLntqa9Cw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:49:50.479050Z"},"content_sha256":"271dcd3e7c428cd0e89462ac344c20f5df71a47abfb4fae2ef7ee46f6e98f8cb","schema_version":"1.0","event_id":"sha256:271dcd3e7c428cd0e89462ac344c20f5df71a47abfb4fae2ef7ee46f6e98f8cb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:7YO7KHAYTJCX66JOYLRO5X47IM","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Antonis Michalas, Khoa Nguyen, Tanveer Khan","submitted_at":"2023-01-20T19:26:51Z","abstract_excerpt":"Split Learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw data. In this setting, the client initially applies its part of the machine learning model on the raw data to generate activation maps and then sends them to the server to continue the training process. Previous works in the field demonstrated that reconstructing activation maps could result in privacy leakage of client data. In addition to that, existing mitigation techniques that overcome the privacy leakage of SL "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08778","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/2301.08778/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":"2026-07-05T05:34:52Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"inFE1YU+ESzxXNURYKvwljFThGs49W757Ub9OsAmjxsBL3tFe/PiRne6Ff0Py0v0HJmuLCyMMqX54IphpzuvCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T14:49:50.479441Z"},"content_sha256":"8fa4e3dcc7dcfaf55b74940cb4448d4eb525fe769673c2ae31c2a07239056507","schema_version":"1.0","event_id":"sha256:8fa4e3dcc7dcfaf55b74940cb4448d4eb525fe769673c2ae31c2a07239056507"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/7YO7KHAYTJCX66JOYLRO5X47IM/bundle.json","state_url":"https://pith.science/pith/7YO7KHAYTJCX66JOYLRO5X47IM/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/7YO7KHAYTJCX66JOYLRO5X47IM/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":"2026-07-06T14:49:50Z","links":{"resolver":"https://pith.science/pith/7YO7KHAYTJCX66JOYLRO5X47IM","bundle":"https://pith.science/pith/7YO7KHAYTJCX66JOYLRO5X47IM/bundle.json","state":"https://pith.science/pith/7YO7KHAYTJCX66JOYLRO5X47IM/state.json","well_known_bundle":"https://pith.science/.well-known/pith/7YO7KHAYTJCX66JOYLRO5X47IM/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:7YO7KHAYTJCX66JOYLRO5X47IM","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":"985db96f8f2c933a4b0f5c85118a87893244fcc803a3a3585e27628b6654e305","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-01-20T19:26:51Z","title_canon_sha256":"4af12f782ceed7da9c28f0302c5546127171cf0255b020e2c0aad71ed4d40221"},"schema_version":"1.0","source":{"id":"2301.08778","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.08778","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"arxiv_version","alias_value":"2301.08778v1","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.08778","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_12","alias_value":"7YO7KHAYTJCX","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_16","alias_value":"7YO7KHAYTJCX66JO","created_at":"2026-07-05T05:34:52Z"},{"alias_kind":"pith_short_8","alias_value":"7YO7KHAY","created_at":"2026-07-05T05:34:52Z"}],"graph_snapshots":[{"event_id":"sha256:8fa4e3dcc7dcfaf55b74940cb4448d4eb525fe769673c2ae31c2a07239056507","target":"graph","created_at":"2026-07-05T05:34:52Z","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/2301.08778/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Split Learning (SL) is a new collaborative learning technique that allows participants, e.g. a client and a server, to train machine learning models without the client sharing raw data. In this setting, the client initially applies its part of the machine learning model on the raw data to generate activation maps and then sends them to the server to continue the training process. Previous works in the field demonstrated that reconstructing activation maps could result in privacy leakage of client data. In addition to that, existing mitigation techniques that overcome the privacy leakage of SL ","authors_text":"Antonis Michalas, Khoa Nguyen, Tanveer Khan","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-01-20T19:26:51Z","title":"Split Ways: Privacy-Preserving Training of Encrypted Data Using Split Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.08778","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":"sha256:271dcd3e7c428cd0e89462ac344c20f5df71a47abfb4fae2ef7ee46f6e98f8cb","target":"record","created_at":"2026-07-05T05:34:52Z","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":"985db96f8f2c933a4b0f5c85118a87893244fcc803a3a3585e27628b6654e305","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2023-01-20T19:26:51Z","title_canon_sha256":"4af12f782ceed7da9c28f0302c5546127171cf0255b020e2c0aad71ed4d40221"},"schema_version":"1.0","source":{"id":"2301.08778","kind":"arxiv","version":1}},"canonical_sha256":"fe1df51c189a457f792ec2e2eedf9f43282b835db5c40fbae2b872cfdb6bd0b1","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"fe1df51c189a457f792ec2e2eedf9f43282b835db5c40fbae2b872cfdb6bd0b1","first_computed_at":"2026-07-05T05:34:52.686638Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:34:52.686638Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N69tK7ZtDI6i8Uo9nbmMOSZGG2bd2Z60C7xSdVA7OCNEP+SzvbxU4ZNU3f0IFnDzxgPdoBsINV7z/ZE27KPJDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:34:52.687096Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.08778","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:271dcd3e7c428cd0e89462ac344c20f5df71a47abfb4fae2ef7ee46f6e98f8cb","sha256:8fa4e3dcc7dcfaf55b74940cb4448d4eb525fe769673c2ae31c2a07239056507"],"state_sha256":"a732890e917bc649844de3cf4757c49d5b17a717e1823b1731c9b159a8c9e7a6"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"om9rQ0m2P6xby+Bh3ewDzC1oAHeFGwP327QnBr9PW2mgKi+QzQMsNM+q6qswhykRFyShz+uSNFhq9EOojkoLCg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T14:49:50.481402Z","bundle_sha256":"4c3de41630498975e36ff76050026224834c8daec66e8688901ec84e25cb9fe8"}}