{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:GCSLMVKTE7I2ZTRK4TK4PZLROU","short_pith_number":"pith:GCSLMVKT","canonical_record":{"source":{"id":"2003.12365","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2020-03-16T06:06:14Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"261cece55d44a98949b24e0815609d1e0e7277f88ec645d788692541c9e5ffaf","abstract_canon_sha256":"f803da04dbd62c8913345c35cc0b4c9843aacbd178474351b07c30c6c883553c"},"schema_version":"1.0"},"canonical_sha256":"30a4b6555327d1acce2ae4d5c7e57175234827a146a0ef74b03a88eaf7fcd449","source":{"kind":"arxiv","id":"2003.12365","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.12365","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"arxiv_version","alias_value":"2003.12365v1","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.12365","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_12","alias_value":"GCSLMVKTE7I2","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_16","alias_value":"GCSLMVKTE7I2ZTRK","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_8","alias_value":"GCSLMVKT","created_at":"2026-07-05T00:50:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:GCSLMVKTE7I2ZTRK4TK4PZLROU","target":"record","payload":{"canonical_record":{"source":{"id":"2003.12365","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2020-03-16T06:06:14Z","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"title_canon_sha256":"261cece55d44a98949b24e0815609d1e0e7277f88ec645d788692541c9e5ffaf","abstract_canon_sha256":"f803da04dbd62c8913345c35cc0b4c9843aacbd178474351b07c30c6c883553c"},"schema_version":"1.0"},"canonical_sha256":"30a4b6555327d1acce2ae4d5c7e57175234827a146a0ef74b03a88eaf7fcd449","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:50:57.697495Z","signature_b64":"ddBNNa/EMgIHtUF2I+P3WCkJ68iAeLIjmsaGmrGKKiY8Pk50Teu3fF8K9OgaoqyxkJMRZOb5yXYjKnWyz3BDAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"30a4b6555327d1acce2ae4d5c7e57175234827a146a0ef74b03a88eaf7fcd449","last_reissued_at":"2026-07-05T00:50:57.697153Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:50:57.697153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2003.12365","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":"2026-07-05T00:50:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x6I2mqKeCGcMWffsWXRBDCzxcdwTjn5i4g6ssjhBjXFHNkB8Y/rZ26dRqOx4ic+a3mJj8X/W/tk9t29vbfz0Cg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T17:51:49.331326Z"},"content_sha256":"246758b978d3fad7f0a130fad9f053dc9eba5dcae08d770c85c4ea98c4b141c3","schema_version":"1.0","event_id":"sha256:246758b978d3fad7f0a130fad9f053dc9eba5dcae08d770c85c4ea98c4b141c3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:GCSLMVKTE7I2ZTRK4TK4PZLROU","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","cs.NE","stat.ML"],"primary_cat":"cs.CR","authors_text":"Chandra Thapa, Hyoungshick Kim, Kyuyeon Kim, Minki Kim, Seyit A. Camtepe, Sharif Abuadbba, Surya Nepal, Yansong Gao","submitted_at":"2020-03-16T06:06:14Z","abstract_excerpt":"A new collaborative learning, called split learning, was recently introduced, aiming to protect user data privacy without revealing raw input data to a server. It collaboratively runs a deep neural network model where the model is split into two parts, one for the client and the other for the server. Therefore, the server has no direct access to raw data processed at the client. Until now, the split learning is believed to be a promising approach to protect the client's raw data; for example, the client's data was protected in healthcare image applications using 2D convolutional neural network"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.12365","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/2003.12365/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":"2026-07-05T00:50:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"gAqcpZOGRieXjrWw61RR0bzT2ekgQUtsFPvKJbZJgw6fhyvszhu2996BIRg9abjSRxgMVKvPqXonQsanG94UCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-22T17:51:49.331833Z"},"content_sha256":"81af411ba836b0b44e03541af2e49f2677e009ce9bbdd350c86bab9ffcd3bc3e","schema_version":"1.0","event_id":"sha256:81af411ba836b0b44e03541af2e49f2677e009ce9bbdd350c86bab9ffcd3bc3e"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/bundle.json","state_url":"https://pith.science/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/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":"2026-08-22T17:51:49Z","links":{"resolver":"https://pith.science/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU","bundle":"https://pith.science/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/bundle.json","state":"https://pith.science/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/state.json","well_known_bundle":"https://pith.science/.well-known/pith/GCSLMVKTE7I2ZTRK4TK4PZLROU/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:GCSLMVKTE7I2ZTRK4TK4PZLROU","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":"f803da04dbd62c8913345c35cc0b4c9843aacbd178474351b07c30c6c883553c","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2020-03-16T06:06:14Z","title_canon_sha256":"261cece55d44a98949b24e0815609d1e0e7277f88ec645d788692541c9e5ffaf"},"schema_version":"1.0","source":{"id":"2003.12365","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2003.12365","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"arxiv_version","alias_value":"2003.12365v1","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2003.12365","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_12","alias_value":"GCSLMVKTE7I2","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_16","alias_value":"GCSLMVKTE7I2ZTRK","created_at":"2026-07-05T00:50:57Z"},{"alias_kind":"pith_short_8","alias_value":"GCSLMVKT","created_at":"2026-07-05T00:50:57Z"}],"graph_snapshots":[{"event_id":"sha256:81af411ba836b0b44e03541af2e49f2677e009ce9bbdd350c86bab9ffcd3bc3e","target":"graph","created_at":"2026-07-05T00:50:57Z","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/2003.12365/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"A new collaborative learning, called split learning, was recently introduced, aiming to protect user data privacy without revealing raw input data to a server. It collaboratively runs a deep neural network model where the model is split into two parts, one for the client and the other for the server. Therefore, the server has no direct access to raw data processed at the client. Until now, the split learning is believed to be a promising approach to protect the client's raw data; for example, the client's data was protected in healthcare image applications using 2D convolutional neural network","authors_text":"Chandra Thapa, Hyoungshick Kim, Kyuyeon Kim, Minki Kim, Seyit A. Camtepe, Sharif Abuadbba, Surya Nepal, Yansong Gao","cross_cats":["cs.LG","cs.NE","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2020-03-16T06:06:14Z","title":"Can We Use Split Learning on 1D CNN Models for Privacy Preserving Training?"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2003.12365","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":"sha256:246758b978d3fad7f0a130fad9f053dc9eba5dcae08d770c85c4ea98c4b141c3","target":"record","created_at":"2026-07-05T00:50:57Z","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":"f803da04dbd62c8913345c35cc0b4c9843aacbd178474351b07c30c6c883553c","cross_cats_sorted":["cs.LG","cs.NE","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2020-03-16T06:06:14Z","title_canon_sha256":"261cece55d44a98949b24e0815609d1e0e7277f88ec645d788692541c9e5ffaf"},"schema_version":"1.0","source":{"id":"2003.12365","kind":"arxiv","version":1}},"canonical_sha256":"30a4b6555327d1acce2ae4d5c7e57175234827a146a0ef74b03a88eaf7fcd449","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"30a4b6555327d1acce2ae4d5c7e57175234827a146a0ef74b03a88eaf7fcd449","first_computed_at":"2026-07-05T00:50:57.697153Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:50:57.697153Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"ddBNNa/EMgIHtUF2I+P3WCkJ68iAeLIjmsaGmrGKKiY8Pk50Teu3fF8K9OgaoqyxkJMRZOb5yXYjKnWyz3BDAA==","signature_status":"signed_v1","signed_at":"2026-07-05T00:50:57.697495Z","signed_message":"canonical_sha256_bytes"},"source_id":"2003.12365","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:246758b978d3fad7f0a130fad9f053dc9eba5dcae08d770c85c4ea98c4b141c3","sha256:81af411ba836b0b44e03541af2e49f2677e009ce9bbdd350c86bab9ffcd3bc3e"],"state_sha256":"3dad3c57e59092af76b611738a3174ac13c3d0168a00e44988fb8d6f6c0848b3"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3wcN1RHLmUKXP/ONCo2IlPoNaDu4YB+frg2dYJg/8aDHEcBhECbQ57YSWtZMpVe65doSG7apu42Be2n7NORDAg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-22T17:51:49.335728Z","bundle_sha256":"96dadb5d3b499534f28f0fb054c8b767f1429fee446c5563537c68ce53ba1723"}}