{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:LUQXUDCV6A6YN5WPFPO2VXRP65","short_pith_number":"pith:LUQXUDCV","canonical_record":{"source":{"id":"1907.06034","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-07-13T09:17:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"21ec91191b5f8e0810584376b68ddf7ea2f3c5f3d1f92c0b86d03cfe99b918e5","abstract_canon_sha256":"da222bbde2a75a4011b2d688e3798c83e68ce673c27e29ea5577c7e3cb249dfb"},"schema_version":"1.0"},"canonical_sha256":"5d217a0c55f03d86f6cf2bddaade2ff777b5e521d5eb209f1c3e49404c63491f","source":{"kind":"arxiv","id":"1907.06034","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06034","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06034v1","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06034","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"pith_short_12","alias_value":"LUQXUDCV6A6Y","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LUQXUDCV6A6YN5WP","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LUQXUDCV","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:LUQXUDCV6A6YN5WPFPO2VXRP65","target":"record","payload":{"canonical_record":{"source":{"id":"1907.06034","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-07-13T09:17:57Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"21ec91191b5f8e0810584376b68ddf7ea2f3c5f3d1f92c0b86d03cfe99b918e5","abstract_canon_sha256":"da222bbde2a75a4011b2d688e3798c83e68ce673c27e29ea5577c7e3cb249dfb"},"schema_version":"1.0"},"canonical_sha256":"5d217a0c55f03d86f6cf2bddaade2ff777b5e521d5eb209f1c3e49404c63491f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:42.629533Z","signature_b64":"rx+Z5NK1Ven77Pj2wpoY+xonnDLoETAeCrjoGwTQ0u6p3ODDWxTLhVW4dxBzCZN6kQ7PeWi9LHBz79+cDyffBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5d217a0c55f03d86f6cf2bddaade2ff777b5e521d5eb209f1c3e49404c63491f","last_reissued_at":"2026-05-17T23:40:42.628494Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:42.628494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.06034","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":"2026-05-17T23:40:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nzGBLtoC4ExaMirilXoo2DBOAsHQhEb61vvdoYLtZObUGZikSXRRpXKIqh7fMnT7CZZwDx2VkwXEl7F22ZKhAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T22:47:49.539192Z"},"content_sha256":"e55c0a8bdef4e60a0681dc024aaa4785ae90d47cf57347fdfde85f9bb884463f","schema_version":"1.0","event_id":"sha256:e55c0a8bdef4e60a0681dc024aaa4785ae90d47cf57347fdfde85f9bb884463f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:LUQXUDCV6A6YN5WPFPO2VXRP65","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Characterizing and Limiting Information Exposure in DNN Layers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.CR","authors_text":"Ali Shahin Shamsabadi, Andrea Cavallaro, Fan Mo, Hamed Haddadi, Kleomenis Katevas","submitted_at":"2019-07-13T09:17:57Z","abstract_excerpt":"Pre-trained Deep Neural Network (DNN) models are increasingly used in smartphones and other user devices to enable prediction services, leading to potential disclosures of (sensitive) information from training data captured inside these models. Based on the concept of generalization error, we propose a framework to measure the amount of sensitive information memorized in each layer of a DNN. Our results show that, when considered individually, the last layers encode a larger amount of information from the training data compared to the first layers. We find that, while the neuron of convolution"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06034","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":""},"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":"2026-05-17T23:40:42Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"O5P/iviNPmUtTQ8ahFEmZjbTyY+lLS3muA9fLn0vy9z0xZ+Y/OT0c+QpwW2QaQBlWh8UcqYv5zKNxnWRQrirAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T22:47:49.539605Z"},"content_sha256":"f1310233ef4dc1c1353cc4f1670b13a7d30713a9d52262bd64921ba1e26669ad","schema_version":"1.0","event_id":"sha256:f1310233ef4dc1c1353cc4f1670b13a7d30713a9d52262bd64921ba1e26669ad"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/bundle.json","state_url":"https://pith.science/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/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":"2026-05-20T22:47:49Z","links":{"resolver":"https://pith.science/pith/LUQXUDCV6A6YN5WPFPO2VXRP65","bundle":"https://pith.science/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/bundle.json","state":"https://pith.science/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/state.json","well_known_bundle":"https://pith.science/.well-known/pith/LUQXUDCV6A6YN5WPFPO2VXRP65/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:LUQXUDCV6A6YN5WPFPO2VXRP65","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":"da222bbde2a75a4011b2d688e3798c83e68ce673c27e29ea5577c7e3cb249dfb","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-07-13T09:17:57Z","title_canon_sha256":"21ec91191b5f8e0810584376b68ddf7ea2f3c5f3d1f92c0b86d03cfe99b918e5"},"schema_version":"1.0","source":{"id":"1907.06034","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06034","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06034v1","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06034","created_at":"2026-05-17T23:40:42Z"},{"alias_kind":"pith_short_12","alias_value":"LUQXUDCV6A6Y","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"LUQXUDCV6A6YN5WP","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"LUQXUDCV","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:f1310233ef4dc1c1353cc4f1670b13a7d30713a9d52262bd64921ba1e26669ad","target":"graph","created_at":"2026-05-17T23:40:42Z","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"},"paper":{"abstract_excerpt":"Pre-trained Deep Neural Network (DNN) models are increasingly used in smartphones and other user devices to enable prediction services, leading to potential disclosures of (sensitive) information from training data captured inside these models. Based on the concept of generalization error, we propose a framework to measure the amount of sensitive information memorized in each layer of a DNN. Our results show that, when considered individually, the last layers encode a larger amount of information from the training data compared to the first layers. We find that, while the neuron of convolution","authors_text":"Ali Shahin Shamsabadi, Andrea Cavallaro, Fan Mo, Hamed Haddadi, Kleomenis Katevas","cross_cats":["cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-07-13T09:17:57Z","title":"Towards Characterizing and Limiting Information Exposure in DNN Layers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06034","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:e55c0a8bdef4e60a0681dc024aaa4785ae90d47cf57347fdfde85f9bb884463f","target":"record","created_at":"2026-05-17T23:40:42Z","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":"da222bbde2a75a4011b2d688e3798c83e68ce673c27e29ea5577c7e3cb249dfb","cross_cats_sorted":["cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-07-13T09:17:57Z","title_canon_sha256":"21ec91191b5f8e0810584376b68ddf7ea2f3c5f3d1f92c0b86d03cfe99b918e5"},"schema_version":"1.0","source":{"id":"1907.06034","kind":"arxiv","version":1}},"canonical_sha256":"5d217a0c55f03d86f6cf2bddaade2ff777b5e521d5eb209f1c3e49404c63491f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5d217a0c55f03d86f6cf2bddaade2ff777b5e521d5eb209f1c3e49404c63491f","first_computed_at":"2026-05-17T23:40:42.628494Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:42.628494Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rx+Z5NK1Ven77Pj2wpoY+xonnDLoETAeCrjoGwTQ0u6p3ODDWxTLhVW4dxBzCZN6kQ7PeWi9LHBz79+cDyffBQ==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:42.629533Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.06034","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:e55c0a8bdef4e60a0681dc024aaa4785ae90d47cf57347fdfde85f9bb884463f","sha256:f1310233ef4dc1c1353cc4f1670b13a7d30713a9d52262bd64921ba1e26669ad"],"state_sha256":"d5a0491595bf28e6edae3c9db05f0b336efde0c2a79becc42209e1141bb57918"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"q69wdXnC6X9jRFoCeGKOAf4QMXHHYf1LlJxfjwsRAbY/A1zKcCXdYSE4auXQzN0BOQWNZrlNa0Dr/FOFxCAYCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T22:47:49.543803Z","bundle_sha256":"bd6f5d6c11e0fc7833105bb62e10fee45497f0a37e068e0c905a894b507d9bc9"}}