{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2018:RP5QMMLWN2DI2QDWMOT2VSGOIY","short_pith_number":"pith:RP5QMMLW","canonical_record":{"source":{"id":"1811.04422","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-11T14:28:34Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4801fd5cb79fe977f8df321a1e230626c9e7ab1e564f7c3d9be29801a33b1b57","abstract_canon_sha256":"b2d9aff7a568a4cfa6e880b0b159dc52cdcdd4de13f29d3231345867f43f0e3c"},"schema_version":"1.0"},"canonical_sha256":"8bfb0631766e868d407663a7aac8ce46130df880bf7ed6238f4bf2b7ffce0751","source":{"kind":"arxiv","id":"1811.04422","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.04422","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"arxiv_version","alias_value":"1811.04422v1","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.04422","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"pith_short_12","alias_value":"RP5QMMLWN2DI","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RP5QMMLWN2DI2QDW","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RP5QMMLW","created_at":"2026-05-18T12:32:50Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2018:RP5QMMLWN2DI2QDWMOT2VSGOIY","target":"record","payload":{"canonical_record":{"source":{"id":"1811.04422","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-11T14:28:34Z","cross_cats_sorted":["stat.ML"],"title_canon_sha256":"4801fd5cb79fe977f8df321a1e230626c9e7ab1e564f7c3d9be29801a33b1b57","abstract_canon_sha256":"b2d9aff7a568a4cfa6e880b0b159dc52cdcdd4de13f29d3231345867f43f0e3c"},"schema_version":"1.0"},"canonical_sha256":"8bfb0631766e868d407663a7aac8ce46130df880bf7ed6238f4bf2b7ffce0751","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:01:05.212228Z","signature_b64":"Kum495pB7hfyWKaBcKtUO5LciWaDO6tPcX4iuixGxw20/9E+SumsMm4dN6UsufLKSjEgUdH2ffY9q/oo5rHfAw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"8bfb0631766e868d407663a7aac8ce46130df880bf7ed6238f4bf2b7ffce0751","last_reissued_at":"2026-05-18T00:01:05.211580Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:01:05.211580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1811.04422","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":"2026-05-18T00:01:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"5/DZu2gRANgLWK7iS0gTP9eIXaWwIJn3DXev2Hdc2LjxRIbZKBSllUkfQ00kkZs+ZJMYULd5GMU0udDPgACnCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T05:58:43.483014Z"},"content_sha256":"ac054d9a0e071d9aa524ae77f25fa39a5a9b38d31fa76736f957c4bb86e2e13f","schema_version":"1.0","event_id":"sha256:ac054d9a0e071d9aa524ae77f25fa39a5a9b38d31fa76736f957c4bb86e2e13f"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2018:RP5QMMLWN2DI2QDWMOT2VSGOIY","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"An Optimal Control View of Adversarial Machine Learning","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["stat.ML"],"primary_cat":"cs.LG","authors_text":"Xiaojin Zhu","submitted_at":"2018-11-11T14:28:34Z","abstract_excerpt":"I describe an optimal control view of adversarial machine learning, where the dynamical system is the machine learner, the input are adversarial actions, and the control costs are defined by the adversary's goals to do harm and be hard to detect. This view encompasses many types of adversarial machine learning, including test-item attacks, training-data poisoning, and adversarial reward shaping. The view encourages adversarial machine learning researcher to utilize advances in control theory and reinforcement learning."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.04422","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":"2026-05-18T00:01:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"WJjJApsJ/5G6IJgDjCKiOHANjMqO0ne5lfEW9+6ASMr+QqRZ2ckeFnS0knJ2otYf3v60+IthYWQYIe7cWVrYDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-12T05:58:43.483356Z"},"content_sha256":"4dcff7c5fae589a9c2ece3b97a0fb65267b0a1f13b75fa9069ac1422f0cba812","schema_version":"1.0","event_id":"sha256:4dcff7c5fae589a9c2ece3b97a0fb65267b0a1f13b75fa9069ac1422f0cba812"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/bundle.json","state_url":"https://pith.science/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/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":"2026-06-12T05:58:43Z","links":{"resolver":"https://pith.science/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY","bundle":"https://pith.science/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/bundle.json","state":"https://pith.science/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/state.json","well_known_bundle":"https://pith.science/.well-known/pith/RP5QMMLWN2DI2QDWMOT2VSGOIY/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2018:RP5QMMLWN2DI2QDWMOT2VSGOIY","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":"b2d9aff7a568a4cfa6e880b0b159dc52cdcdd4de13f29d3231345867f43f0e3c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-11T14:28:34Z","title_canon_sha256":"4801fd5cb79fe977f8df321a1e230626c9e7ab1e564f7c3d9be29801a33b1b57"},"schema_version":"1.0","source":{"id":"1811.04422","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1811.04422","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"arxiv_version","alias_value":"1811.04422v1","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1811.04422","created_at":"2026-05-18T00:01:05Z"},{"alias_kind":"pith_short_12","alias_value":"RP5QMMLWN2DI","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_16","alias_value":"RP5QMMLWN2DI2QDW","created_at":"2026-05-18T12:32:50Z"},{"alias_kind":"pith_short_8","alias_value":"RP5QMMLW","created_at":"2026-05-18T12:32:50Z"}],"graph_snapshots":[{"event_id":"sha256:4dcff7c5fae589a9c2ece3b97a0fb65267b0a1f13b75fa9069ac1422f0cba812","target":"graph","created_at":"2026-05-18T00:01:05Z","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":"I describe an optimal control view of adversarial machine learning, where the dynamical system is the machine learner, the input are adversarial actions, and the control costs are defined by the adversary's goals to do harm and be hard to detect. This view encompasses many types of adversarial machine learning, including test-item attacks, training-data poisoning, and adversarial reward shaping. The view encourages adversarial machine learning researcher to utilize advances in control theory and reinforcement learning.","authors_text":"Xiaojin Zhu","cross_cats":["stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-11T14:28:34Z","title":"An Optimal Control View of Adversarial Machine Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1811.04422","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:ac054d9a0e071d9aa524ae77f25fa39a5a9b38d31fa76736f957c4bb86e2e13f","target":"record","created_at":"2026-05-18T00:01:05Z","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":"b2d9aff7a568a4cfa6e880b0b159dc52cdcdd4de13f29d3231345867f43f0e3c","cross_cats_sorted":["stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2018-11-11T14:28:34Z","title_canon_sha256":"4801fd5cb79fe977f8df321a1e230626c9e7ab1e564f7c3d9be29801a33b1b57"},"schema_version":"1.0","source":{"id":"1811.04422","kind":"arxiv","version":1}},"canonical_sha256":"8bfb0631766e868d407663a7aac8ce46130df880bf7ed6238f4bf2b7ffce0751","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"8bfb0631766e868d407663a7aac8ce46130df880bf7ed6238f4bf2b7ffce0751","first_computed_at":"2026-05-18T00:01:05.211580Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-18T00:01:05.211580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"Kum495pB7hfyWKaBcKtUO5LciWaDO6tPcX4iuixGxw20/9E+SumsMm4dN6UsufLKSjEgUdH2ffY9q/oo5rHfAw==","signature_status":"signed_v1","signed_at":"2026-05-18T00:01:05.212228Z","signed_message":"canonical_sha256_bytes"},"source_id":"1811.04422","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:ac054d9a0e071d9aa524ae77f25fa39a5a9b38d31fa76736f957c4bb86e2e13f","sha256:4dcff7c5fae589a9c2ece3b97a0fb65267b0a1f13b75fa9069ac1422f0cba812"],"state_sha256":"a9276a0d0de1c11a28614f9bf0e5292bf83b9a9278589450fbe6f584d5c90410"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"sgDO1iLrnCWmvbDCojszs7QuExP64xwTNiddscXYi5pWYrlFVA1Ss8Lrcnuld1GROiwsKZpmHNZvISD7CYq1AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-12T05:58:43.485194Z","bundle_sha256":"7b79ce4a2a6518ab99f4a48cc486a4f333745dfa0d3214cc3c2251be90ff3d89"}}