{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:ZNPFJ6JHJ37AIBWCF4TOYUMW22","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":"72779269e445a148a1e5bc2b54c568949373e71b002949eeefe5a6882401de09","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2019-10-14T05:04:37Z","title_canon_sha256":"3b0e1c1b57df83b956ac5b30f7e83af71a38def7fa0dc0dd82d507eb6d570f0e"},"schema_version":"1.0","source":{"id":"1910.06838","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1910.06838","created_at":"2026-07-05T00:12:15Z"},{"alias_kind":"arxiv_version","alias_value":"1910.06838v1","created_at":"2026-07-05T00:12:15Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1910.06838","created_at":"2026-07-05T00:12:15Z"},{"alias_kind":"pith_short_12","alias_value":"ZNPFJ6JHJ37A","created_at":"2026-07-05T00:12:15Z"},{"alias_kind":"pith_short_16","alias_value":"ZNPFJ6JHJ37AIBWC","created_at":"2026-07-05T00:12:15Z"},{"alias_kind":"pith_short_8","alias_value":"ZNPFJ6JH","created_at":"2026-07-05T00:12:15Z"}],"graph_snapshots":[{"event_id":"sha256:9020127346c5b8a1d726c72ea7549b7c5fc10f2988ee4c3d9954a6bde7810fce","target":"graph","created_at":"2026-07-05T00:12:15Z","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/1910.06838/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Neural Networks (DNNs) are vulnerable to deliberately crafted adversarial examples. In the past few years, many efforts have been spent on exploring query-optimisation attacks to find adversarial examples of either black-box or white-box DNN models, as well as the defending countermeasures against those attacks. In this work, we explore vulnerabilities of DNN models under the umbrella of Man-in-the-Middle (MitM) attacks, which has not been investigated before. From the perspective of an MitM adversary, the aforementioned adversarial example attacks are not viable anymore. First, such atta","authors_text":"Chaoran Li, Derui (Derek) Wang, Sheng Wen, Surya Nepal, Yang Xiang","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2019-10-14T05:04:37Z","title":"Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1910.06838","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":"sha256:1abbcf82945622831c0a6850108e714adb1bc7b53e8b3c422f49682ac1e8b688","target":"record","created_at":"2026-07-05T00:12:15Z","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":"72779269e445a148a1e5bc2b54c568949373e71b002949eeefe5a6882401de09","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.CR","submitted_at":"2019-10-14T05:04:37Z","title_canon_sha256":"3b0e1c1b57df83b956ac5b30f7e83af71a38def7fa0dc0dd82d507eb6d570f0e"},"schema_version":"1.0","source":{"id":"1910.06838","kind":"arxiv","version":1}},"canonical_sha256":"cb5e54f9274efe0406c22f26ec5196d6a7b25fdde08efb6e8d84cbffff4d2a3e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"cb5e54f9274efe0406c22f26ec5196d6a7b25fdde08efb6e8d84cbffff4d2a3e","first_computed_at":"2026-07-05T00:12:15.848816Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T00:12:15.848816Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"H3r61FpMQHQrWP71HtcVP5OS20o83p81kdP3zS/HKdMBQIXYwkKS0J+1YLkZxV8b9kQK6zvduJYpeIChQG6GDw==","signature_status":"signed_v1","signed_at":"2026-07-05T00:12:15.849211Z","signed_message":"canonical_sha256_bytes"},"source_id":"1910.06838","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:1abbcf82945622831c0a6850108e714adb1bc7b53e8b3c422f49682ac1e8b688","sha256:9020127346c5b8a1d726c72ea7549b7c5fc10f2988ee4c3d9954a6bde7810fce"],"state_sha256":"993965003e9ac4ff0fa08aa05ed3054b64699b30d68df014ac312597f36ea3b3"}