{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:OITUPDBBHT6XMT52ZM7KMUMEIT","short_pith_number":"pith:OITUPDBB","canonical_record":{"source":{"id":"1912.05391","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-11T15:32:45Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"282a226ede7deda07ac412ed96463ffff84a78203e9098b222d85fe676114600","abstract_canon_sha256":"bd6107128a25fe6b083a7ee1f8d76adc641272370cb17c734b3c33a6da230d88"},"schema_version":"1.0"},"canonical_sha256":"7227478c213cfd764fbacb3ea6518444d5e6b0c25fc580d28bff680c972d780e","source":{"kind":"arxiv","id":"1912.05391","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.05391","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"arxiv_version","alias_value":"1912.05391v2","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.05391","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_12","alias_value":"OITUPDBBHT6X","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_16","alias_value":"OITUPDBBHT6XMT52","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_8","alias_value":"OITUPDBB","created_at":"2026-07-05T00:28:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:OITUPDBBHT6XMT52ZM7KMUMEIT","target":"record","payload":{"canonical_record":{"source":{"id":"1912.05391","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-11T15:32:45Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"282a226ede7deda07ac412ed96463ffff84a78203e9098b222d85fe676114600","abstract_canon_sha256":"bd6107128a25fe6b083a7ee1f8d76adc641272370cb17c734b3c33a6da230d88"},"schema_version":"1.0"},"canonical_sha256":"7227478c213cfd764fbacb3ea6518444d5e6b0c25fc580d28bff680c972d780e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:28:57.657859Z","signature_b64":"zKBtXidknZN/5mFe1XQhSJLwnqN04Xgx9g7O1RqgA55mlDq7OGKfFbycU5m2Rt2X5t+itG8xMYb4ePfanN9JAQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"7227478c213cfd764fbacb3ea6518444d5e6b0c25fc580d28bff680c972d780e","last_reissued_at":"2026-07-05T00:28:57.657406Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:28:57.657406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.05391","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:28:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8kWThSwiE7EFLTmRDFcQ4lhLRqZtf60DyORaWaANeBTCgkhV63cMFXshAXqeRVBThnO/Ofb7mRD785Y8qqLCAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:26:57.093198Z"},"content_sha256":"6b7319963d42e8d69526a9d28d420440b5d7bed732176774f4ec1ed2e4f256e5","schema_version":"1.0","event_id":"sha256:6b7319963d42e8d69526a9d28d420440b5d7bed732176774f4ec1ed2e4f256e5"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:OITUPDBBHT6XMT52ZM7KMUMEIT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Detecting and Correcting Adversarial Images Using Image Processing Operations","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Huy H. Nguyen, Isao Echizen, Junichi Yamagishi, Minoru Kuribayashi","submitted_at":"2019-12-11T15:32:45Z","abstract_excerpt":"Deep neural networks (DNNs) have achieved excellent performance on several tasks and have been widely applied in both academia and industry. However, DNNs are vulnerable to adversarial machine learning attacks, in which noise is added to the input to change the network output. We have devised an image-processing-based method to detect adversarial images based on our observation that adversarial noise is reduced after applying these operations while the normal images almost remain unaffected. In addition to detection, this method can be used to restore the adversarial images' original labels, w"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.05391","kind":"arxiv","version":2},"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/1912.05391/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":"2026-07-05T00:28:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"hJWMKJlfyeo40uF/GYSgM7C0PEnXkz4GGsrGEHUNAQtYrTZ9oMmYweq9JS6HRIzMLsrZCHRUqPPLaeBtQF41Bw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-05T20:26:57.093791Z"},"content_sha256":"878da93b0e436e862f84efd7a17aaf0ed322988e3bde9eeb89ba7b57cf643bf1","schema_version":"1.0","event_id":"sha256:878da93b0e436e862f84efd7a17aaf0ed322988e3bde9eeb89ba7b57cf643bf1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/bundle.json","state_url":"https://pith.science/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/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":"2026-08-05T20:26:57Z","links":{"resolver":"https://pith.science/pith/OITUPDBBHT6XMT52ZM7KMUMEIT","bundle":"https://pith.science/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/bundle.json","state":"https://pith.science/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OITUPDBBHT6XMT52ZM7KMUMEIT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:OITUPDBBHT6XMT52ZM7KMUMEIT","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":"bd6107128a25fe6b083a7ee1f8d76adc641272370cb17c734b3c33a6da230d88","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-11T15:32:45Z","title_canon_sha256":"282a226ede7deda07ac412ed96463ffff84a78203e9098b222d85fe676114600"},"schema_version":"1.0","source":{"id":"1912.05391","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.05391","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"arxiv_version","alias_value":"1912.05391v2","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.05391","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_12","alias_value":"OITUPDBBHT6X","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_16","alias_value":"OITUPDBBHT6XMT52","created_at":"2026-07-05T00:28:57Z"},{"alias_kind":"pith_short_8","alias_value":"OITUPDBB","created_at":"2026-07-05T00:28:57Z"}],"graph_snapshots":[{"event_id":"sha256:878da93b0e436e862f84efd7a17aaf0ed322988e3bde9eeb89ba7b57cf643bf1","target":"graph","created_at":"2026-07-05T00:28:57Z","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/1912.05391/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep neural networks (DNNs) have achieved excellent performance on several tasks and have been widely applied in both academia and industry. However, DNNs are vulnerable to adversarial machine learning attacks, in which noise is added to the input to change the network output. We have devised an image-processing-based method to detect adversarial images based on our observation that adversarial noise is reduced after applying these operations while the normal images almost remain unaffected. In addition to detection, this method can be used to restore the adversarial images' original labels, w","authors_text":"Huy H. Nguyen, Isao Echizen, Junichi Yamagishi, Minoru Kuribayashi","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-11T15:32:45Z","title":"Detecting and Correcting Adversarial Images Using Image Processing Operations"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.05391","kind":"arxiv","version":2},"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":"sha256:6b7319963d42e8d69526a9d28d420440b5d7bed732176774f4ec1ed2e4f256e5","target":"record","created_at":"2026-07-05T00:28:57Z","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":"bd6107128a25fe6b083a7ee1f8d76adc641272370cb17c734b3c33a6da230d88","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-11T15:32:45Z","title_canon_sha256":"282a226ede7deda07ac412ed96463ffff84a78203e9098b222d85fe676114600"},"schema_version":"1.0","source":{"id":"1912.05391","kind":"arxiv","version":2}},"canonical_sha256":"7227478c213cfd764fbacb3ea6518444d5e6b0c25fc580d28bff680c972d780e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"7227478c213cfd764fbacb3ea6518444d5e6b0c25fc580d28bff680c972d780e","first_computed_at":"2026-07-05T00:28:57.657406Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:28:57.657406Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"zKBtXidknZN/5mFe1XQhSJLwnqN04Xgx9g7O1RqgA55mlDq7OGKfFbycU5m2Rt2X5t+itG8xMYb4ePfanN9JAQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:28:57.657859Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.05391","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6b7319963d42e8d69526a9d28d420440b5d7bed732176774f4ec1ed2e4f256e5","sha256:878da93b0e436e862f84efd7a17aaf0ed322988e3bde9eeb89ba7b57cf643bf1"],"state_sha256":"139e287d1508e7744d773c5236de1bb3d86f54dc13d4b63b9a0c16ad70e746ec"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"w6siMTarFEG8KkO275QVtjdjo8iwDihUh0CHL9kKy9YGtZcxwhAT9Gc68gy8ECUtGCT6UioRCiOBsqxu/xVPCQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-05T20:26:57.098944Z","bundle_sha256":"2bcb1e872b0c2bcd00ae104e56bba3c9d384b4f2889ec2d6051f8052c393bbe1"}}