{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:YSHMAK4GAOZBTP5DXE5DERM4BV","short_pith_number":"pith:YSHMAK4G","canonical_record":{"source":{"id":"1912.01667","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-03T20:06:49Z","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"title_canon_sha256":"9279101310375a7c58d79f7b1c8e0c3c043f005feb924978c28a04e0f8dd006f","abstract_canon_sha256":"24abebabab1981424e4f57504b82fc16cc048c3f504fee83b1e20db23216c784"},"schema_version":"1.0"},"canonical_sha256":"c48ec02b8603b219bfa3b93a32459c0d49fe3147fdb8115776a0de9aca3b0979","source":{"kind":"arxiv","id":"1912.01667","version":3},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.01667","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"arxiv_version","alias_value":"1912.01667v3","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.01667","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_12","alias_value":"YSHMAK4GAOZB","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_16","alias_value":"YSHMAK4GAOZBTP5D","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_8","alias_value":"YSHMAK4G","created_at":"2026-07-05T00:38:55Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:YSHMAK4GAOZBTP5DXE5DERM4BV","target":"record","payload":{"canonical_record":{"source":{"id":"1912.01667","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-03T20:06:49Z","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"title_canon_sha256":"9279101310375a7c58d79f7b1c8e0c3c043f005feb924978c28a04e0f8dd006f","abstract_canon_sha256":"24abebabab1981424e4f57504b82fc16cc048c3f504fee83b1e20db23216c784"},"schema_version":"1.0"},"canonical_sha256":"c48ec02b8603b219bfa3b93a32459c0d49fe3147fdb8115776a0de9aca3b0979","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:38:55.610998Z","signature_b64":"eGRuNJWo88OKrdBtKgXKz8phHR5uSSugj8wYgkF1gd26O9KckF3h5TAKjbgr7BX/xO45ndjpneWg2h3yMwRoCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c48ec02b8603b219bfa3b93a32459c0d49fe3147fdb8115776a0de9aca3b0979","last_reissued_at":"2026-07-05T00:38:55.610486Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:38:55.610486Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1912.01667","source_version":3,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T00:38:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Uy4JAqi9fhwvVBCDhoh/gc76IglpXalJU4k/tII3i6SAwyFjqiPz8ZA6ALS+BI1UxwcQK1jZxV/+0PpPzycHAQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:26:37.441107Z"},"content_sha256":"d384e3c3eeb1d989a7e74c838020330c34e45ca9d255aaf612ef1f5202ad21e7","schema_version":"1.0","event_id":"sha256:d384e3c3eeb1d989a7e74c838020330c34e45ca9d255aaf612ef1f5202ad21e7"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:YSHMAK4GAOZBTP5DXE5DERM4BV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey of Black-Box Adversarial Attacks on Computer Vision Models","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.CR","cs.CV","stat.ML"],"primary_cat":"cs.LG","authors_text":"Arun Balaji Buduru, Avinash Tulasi, Siddhant Bhambri, Sumanyu Muku","submitted_at":"2019-12-03T20:06:49Z","abstract_excerpt":"Machine learning has seen tremendous advances in the past few years, which has lead to deep learning models being deployed in varied applications of day-to-day life. Attacks on such models using perturbations, particularly in real-life scenarios, pose a severe challenge to their applicability, pushing research into the direction which aims to enhance the robustness of these models. After the introduction of these perturbations by Szegedy et al. [1], significant amount of research has focused on the reliability of such models, primarily in two aspects - white-box, where the adversary has access"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.01667","kind":"arxiv","version":3},"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/1912.01667/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":"2026-07-05T00:38:55Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lBBksztVsvfQup3Gsdtjb3n0bVaRZUE41FSsFCVDMikz7D0esUGXCUmvLds+n4POycYF6jL0IcgYul7ZmIifCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T16:26:37.441498Z"},"content_sha256":"685b2f4b80e374c847789f78586681bc6499fba0181f60a78475867aa22a25f1","schema_version":"1.0","event_id":"sha256:685b2f4b80e374c847789f78586681bc6499fba0181f60a78475867aa22a25f1"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/bundle.json","state_url":"https://pith.science/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/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":"2026-07-08T16:26:37Z","links":{"resolver":"https://pith.science/pith/YSHMAK4GAOZBTP5DXE5DERM4BV","bundle":"https://pith.science/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/bundle.json","state":"https://pith.science/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/YSHMAK4GAOZBTP5DXE5DERM4BV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:YSHMAK4GAOZBTP5DXE5DERM4BV","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":"24abebabab1981424e4f57504b82fc16cc048c3f504fee83b1e20db23216c784","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-03T20:06:49Z","title_canon_sha256":"9279101310375a7c58d79f7b1c8e0c3c043f005feb924978c28a04e0f8dd006f"},"schema_version":"1.0","source":{"id":"1912.01667","kind":"arxiv","version":3}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1912.01667","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"arxiv_version","alias_value":"1912.01667v3","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1912.01667","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_12","alias_value":"YSHMAK4GAOZB","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_16","alias_value":"YSHMAK4GAOZBTP5D","created_at":"2026-07-05T00:38:55Z"},{"alias_kind":"pith_short_8","alias_value":"YSHMAK4G","created_at":"2026-07-05T00:38:55Z"}],"graph_snapshots":[{"event_id":"sha256:685b2f4b80e374c847789f78586681bc6499fba0181f60a78475867aa22a25f1","target":"graph","created_at":"2026-07-05T00:38:55Z","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/1912.01667/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning has seen tremendous advances in the past few years, which has lead to deep learning models being deployed in varied applications of day-to-day life. Attacks on such models using perturbations, particularly in real-life scenarios, pose a severe challenge to their applicability, pushing research into the direction which aims to enhance the robustness of these models. After the introduction of these perturbations by Szegedy et al. [1], significant amount of research has focused on the reliability of such models, primarily in two aspects - white-box, where the adversary has access","authors_text":"Arun Balaji Buduru, Avinash Tulasi, Siddhant Bhambri, Sumanyu Muku","cross_cats":["cs.CR","cs.CV","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-03T20:06:49Z","title":"A Survey of Black-Box Adversarial Attacks on Computer Vision Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1912.01667","kind":"arxiv","version":3},"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:d384e3c3eeb1d989a7e74c838020330c34e45ca9d255aaf612ef1f5202ad21e7","target":"record","created_at":"2026-07-05T00:38:55Z","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":"24abebabab1981424e4f57504b82fc16cc048c3f504fee83b1e20db23216c784","cross_cats_sorted":["cs.CR","cs.CV","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-12-03T20:06:49Z","title_canon_sha256":"9279101310375a7c58d79f7b1c8e0c3c043f005feb924978c28a04e0f8dd006f"},"schema_version":"1.0","source":{"id":"1912.01667","kind":"arxiv","version":3}},"canonical_sha256":"c48ec02b8603b219bfa3b93a32459c0d49fe3147fdb8115776a0de9aca3b0979","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c48ec02b8603b219bfa3b93a32459c0d49fe3147fdb8115776a0de9aca3b0979","first_computed_at":"2026-07-05T00:38:55.610486Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:38:55.610486Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"eGRuNJWo88OKrdBtKgXKz8phHR5uSSugj8wYgkF1gd26O9KckF3h5TAKjbgr7BX/xO45ndjpneWg2h3yMwRoCQ==","signature_status":"signed_v1","signed_at":"2026-07-05T00:38:55.610998Z","signed_message":"canonical_sha256_bytes"},"source_id":"1912.01667","source_kind":"arxiv","source_version":3}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d384e3c3eeb1d989a7e74c838020330c34e45ca9d255aaf612ef1f5202ad21e7","sha256:685b2f4b80e374c847789f78586681bc6499fba0181f60a78475867aa22a25f1"],"state_sha256":"aac9e701b02c7a2aad97b1a01a8b06808151a6595d746eb066d836bc525851ae"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"nrLQsQr5BcaLl0CuOoLikZ7CQYF0rLkfjQT+N97gQ3x1T2LGOTLZ/TxbAkKYyl3URkcvfLDjr1cGdrCNRdxqDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T16:26:37.443688Z","bundle_sha256":"7f51d5cfeb9cec8f4722c9cb41386681c1aba237b706721a01f35784fae8668c"}}