{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:L3VXMIBUV2FQWJKL3KIKO5HFBF","short_pith_number":"pith:L3VXMIBU","canonical_record":{"source":{"id":"1907.06291","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T22:20:58Z","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"title_canon_sha256":"b1ba69c6ce27153b90f166604f647a7457068c7543943e9896de38229a74552e","abstract_canon_sha256":"b974efacd28b0f435987b9c6a8199131174344ba0d590d37c642e344cb1ae412"},"schema_version":"1.0"},"canonical_sha256":"5eeb762034ae8b0b254bda90a774e50954ccdfc99df09c4ffa14ad168f1cf3c2","source":{"kind":"arxiv","id":"1907.06291","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06291","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06291v1","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06291","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"pith_short_12","alias_value":"L3VXMIBUV2FQ","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"L3VXMIBUV2FQWJKL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"L3VXMIBU","created_at":"2026-05-18T12:33:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:L3VXMIBUV2FQWJKL3KIKO5HFBF","target":"record","payload":{"canonical_record":{"source":{"id":"1907.06291","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T22:20:58Z","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"title_canon_sha256":"b1ba69c6ce27153b90f166604f647a7457068c7543943e9896de38229a74552e","abstract_canon_sha256":"b974efacd28b0f435987b9c6a8199131174344ba0d590d37c642e344cb1ae412"},"schema_version":"1.0"},"canonical_sha256":"5eeb762034ae8b0b254bda90a774e50954ccdfc99df09c4ffa14ad168f1cf3c2","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:40:38.022219Z","signature_b64":"9V/gP06nJw97bTUdahmsIL7uuKsVFHCyhucCZ//xR34t+Nh3zAbz/eIi6vi/tTjy7exxZdvdDEIH0ZDtOyfBDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"5eeb762034ae8b0b254bda90a774e50954ccdfc99df09c4ffa14ad168f1cf3c2","last_reissued_at":"2026-05-17T23:40:38.021756Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:40:38.021756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1907.06291","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":"2026-05-17T23:40:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zAuj4mXjtUw3R4o/dDB4xqELI1E6b/5tO+Pu7P+jeYbkLlTTNg/PaZAoAmZHW6aCoEXlsPfR6qeFJK5juCRYAg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:52:39.216636Z"},"content_sha256":"efd2ae757a546efa296770c9ecfea4cb2af47861db435438fb8ac857de5472f3","schema_version":"1.0","event_id":"sha256:efd2ae757a546efa296770c9ecfea4cb2af47861db435438fb8ac857de5472f3"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:L3VXMIBUV2FQWJKL3KIKO5HFBF","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Measuring the Transferability of Adversarial Examples","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CR","cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Deyan Petrov, Timothy M. Hospedales","submitted_at":"2019-07-14T22:20:58Z","abstract_excerpt":"Adversarial examples are of wide concern due to their impact on the reliability of contemporary machine learning systems. Effective adversarial examples are mostly found via white-box attacks. However, in some cases they can be transferred across models, thus enabling them to attack black-box models. In this work we evaluate the transferability of three adversarial attacks - the Fast Gradient Sign Method, the Basic Iterative Method, and the Carlini & Wagner method, across two classes of models - the VGG class(using VGG16, VGG19 and an ensemble of VGG16 and VGG19), and the Inception class(Incep"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06291","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":"2026-05-17T23:40:38Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VUjFC0bowiCGP0X8ufAnqDtvyi1+r0hCd4CNDMlWd1CqWrlzgokwPTuCTD8nSMLY67b1MEJmL32vEVSh+FlOAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-26T15:52:39.217370Z"},"content_sha256":"8bbbce29e8bc7fc4dd37ffbf75302a9edf3864f8cfcf935688b37bf55b91ad34","schema_version":"1.0","event_id":"sha256:8bbbce29e8bc7fc4dd37ffbf75302a9edf3864f8cfcf935688b37bf55b91ad34"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/bundle.json","state_url":"https://pith.science/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/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":"2026-05-26T15:52:39Z","links":{"resolver":"https://pith.science/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF","bundle":"https://pith.science/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/bundle.json","state":"https://pith.science/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/state.json","well_known_bundle":"https://pith.science/.well-known/pith/L3VXMIBUV2FQWJKL3KIKO5HFBF/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:L3VXMIBUV2FQWJKL3KIKO5HFBF","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":"b974efacd28b0f435987b9c6a8199131174344ba0d590d37c642e344cb1ae412","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T22:20:58Z","title_canon_sha256":"b1ba69c6ce27153b90f166604f647a7457068c7543943e9896de38229a74552e"},"schema_version":"1.0","source":{"id":"1907.06291","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1907.06291","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"arxiv_version","alias_value":"1907.06291v1","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1907.06291","created_at":"2026-05-17T23:40:38Z"},{"alias_kind":"pith_short_12","alias_value":"L3VXMIBUV2FQ","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_16","alias_value":"L3VXMIBUV2FQWJKL","created_at":"2026-05-18T12:33:21Z"},{"alias_kind":"pith_short_8","alias_value":"L3VXMIBU","created_at":"2026-05-18T12:33:21Z"}],"graph_snapshots":[{"event_id":"sha256:8bbbce29e8bc7fc4dd37ffbf75302a9edf3864f8cfcf935688b37bf55b91ad34","target":"graph","created_at":"2026-05-17T23:40:38Z","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":"Adversarial examples are of wide concern due to their impact on the reliability of contemporary machine learning systems. Effective adversarial examples are mostly found via white-box attacks. However, in some cases they can be transferred across models, thus enabling them to attack black-box models. In this work we evaluate the transferability of three adversarial attacks - the Fast Gradient Sign Method, the Basic Iterative Method, and the Carlini & Wagner method, across two classes of models - the VGG class(using VGG16, VGG19 and an ensemble of VGG16 and VGG19), and the Inception class(Incep","authors_text":"Deyan Petrov, Timothy M. Hospedales","cross_cats":["cs.CR","cs.CV","stat.ML"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T22:20:58Z","title":"Measuring the Transferability of Adversarial Examples"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1907.06291","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:efd2ae757a546efa296770c9ecfea4cb2af47861db435438fb8ac857de5472f3","target":"record","created_at":"2026-05-17T23:40:38Z","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":"b974efacd28b0f435987b9c6a8199131174344ba0d590d37c642e344cb1ae412","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.LG","submitted_at":"2019-07-14T22:20:58Z","title_canon_sha256":"b1ba69c6ce27153b90f166604f647a7457068c7543943e9896de38229a74552e"},"schema_version":"1.0","source":{"id":"1907.06291","kind":"arxiv","version":1}},"canonical_sha256":"5eeb762034ae8b0b254bda90a774e50954ccdfc99df09c4ffa14ad168f1cf3c2","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"5eeb762034ae8b0b254bda90a774e50954ccdfc99df09c4ffa14ad168f1cf3c2","first_computed_at":"2026-05-17T23:40:38.021756Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:40:38.021756Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"9V/gP06nJw97bTUdahmsIL7uuKsVFHCyhucCZ//xR34t+Nh3zAbz/eIi6vi/tTjy7exxZdvdDEIH0ZDtOyfBDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:40:38.022219Z","signed_message":"canonical_sha256_bytes"},"source_id":"1907.06291","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:efd2ae757a546efa296770c9ecfea4cb2af47861db435438fb8ac857de5472f3","sha256:8bbbce29e8bc7fc4dd37ffbf75302a9edf3864f8cfcf935688b37bf55b91ad34"],"state_sha256":"518ccd6a4fd6d861fff93ac3ea5e76954508815a1068ad8ab8efac4793261dd4"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lMX576UUnunTEhfW1hWPMOs4HtY8TZ5MqCiLuW2oXoJPeUeMCD43rcWah2DwJav7NJrQkSe3FANfduDMsiJ2Bg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-26T15:52:39.221302Z","bundle_sha256":"74558909981498e108ab42f1b440e4eb8f8d43755e40125d0ad2b90bb82e80ee"}}