{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2019:HLGTIBNH5E3A5OFTH4JBV645B7","short_pith_number":"pith:HLGTIBNH","canonical_record":{"source":{"id":"1903.06638","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-03-01T04:17:32Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"e978e45e85679d537502a675ae7933356a105ab626bb7cb98fe5208bcdf5a3a7","abstract_canon_sha256":"46025c5aad3af83f8059a46fe745eff79c1bced11dbead972962163710d1fed9"},"schema_version":"1.0"},"canonical_sha256":"3acd3405a7e9360eb8b33f121afb9d0fea03beef93db0c50575f4fba1a6f1e5f","source":{"kind":"arxiv","id":"1903.06638","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.06638","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"1903.06638v1","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.06638","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"HLGTIBNH5E3A","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HLGTIBNH5E3A5OFT","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HLGTIBNH","created_at":"2026-05-18T12:33:18Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2019:HLGTIBNH5E3A5OFTH4JBV645B7","target":"record","payload":{"canonical_record":{"source":{"id":"1903.06638","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-03-01T04:17:32Z","cross_cats_sorted":["cs.LG","stat.ML"],"title_canon_sha256":"e978e45e85679d537502a675ae7933356a105ab626bb7cb98fe5208bcdf5a3a7","abstract_canon_sha256":"46025c5aad3af83f8059a46fe745eff79c1bced11dbead972962163710d1fed9"},"schema_version":"1.0"},"canonical_sha256":"3acd3405a7e9360eb8b33f121afb9d0fea03beef93db0c50575f4fba1a6f1e5f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-17T23:51:10.263664Z","signature_b64":"0hr4ijDX+6Hbsil8ZAVig0y/hBVve7D/GlEQrrr+9ScbOvW01dyvpvnnTCvoBFilfWTV1iDAOQSmwWWQ2mVgDw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"3acd3405a7e9360eb8b33f121afb9d0fea03beef93db0c50575f4fba1a6f1e5f","last_reissued_at":"2026-05-17T23:51:10.263063Z","signature_status":"signed_v1","first_computed_at":"2026-05-17T23:51:10.263063Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"1903.06638","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":"2026-05-17T23:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"8GMn43kfpcqdGogYvfm3urrAsDJXmD6Zd5r/FCqpSZ8fW+JAUrQXDLnPNhBLarlV/2LZntUU9yN83ompYe7LCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T15:28:10.371113Z"},"content_sha256":"a00d5872087fd4066d8a46275fb5c423c022a189f8fed1acd572b0ee6b8c6f33","schema_version":"1.0","event_id":"sha256:a00d5872087fd4066d8a46275fb5c423c022a189f8fed1acd572b0ee6b8c6f33"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2019:HLGTIBNH5E3A5OFTH4JBV645B7","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG","stat.ML"],"primary_cat":"cs.CR","authors_text":"Kacper Wardega, Panagiota Kiourti, Susmit Jha, Wenchao Li","submitted_at":"2019-03-01T04:17:32Z","abstract_excerpt":"Recent work has identified that classification models implemented as neural networks are vulnerable to data-poisoning and Trojan attacks at training time. In this work, we show that these training-time vulnerabilities extend to deep reinforcement learning (DRL) agents and can be exploited by an adversary with access to the training process. In particular, we focus on Trojan attacks that augment the function of reinforcement learning policies with hidden behaviors. We demonstrate that such attacks can be implemented through minuscule data poisoning (as little as 0.025% of the training data) and"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.06638","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":"2026-05-17T23:51:10Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g3dKAMJJUpMbosfLenxO7AmuM6XlECKM2mtGXCLKFce/n7kxKY5CeZUhRx4hDIeYg4cm9NRbbBeDwgU/jZ69Bg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-05-20T15:28:10.371485Z"},"content_sha256":"654efc0bcf61def961652ef9965a8c0ba9b9090fb906db9d940315e83856bed5","schema_version":"1.0","event_id":"sha256:654efc0bcf61def961652ef9965a8c0ba9b9090fb906db9d940315e83856bed5"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/HLGTIBNH5E3A5OFTH4JBV645B7/bundle.json","state_url":"https://pith.science/pith/HLGTIBNH5E3A5OFTH4JBV645B7/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/HLGTIBNH5E3A5OFTH4JBV645B7/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":"2026-05-20T15:28:10Z","links":{"resolver":"https://pith.science/pith/HLGTIBNH5E3A5OFTH4JBV645B7","bundle":"https://pith.science/pith/HLGTIBNH5E3A5OFTH4JBV645B7/bundle.json","state":"https://pith.science/pith/HLGTIBNH5E3A5OFTH4JBV645B7/state.json","well_known_bundle":"https://pith.science/.well-known/pith/HLGTIBNH5E3A5OFTH4JBV645B7/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:HLGTIBNH5E3A5OFTH4JBV645B7","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":"46025c5aad3af83f8059a46fe745eff79c1bced11dbead972962163710d1fed9","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-03-01T04:17:32Z","title_canon_sha256":"e978e45e85679d537502a675ae7933356a105ab626bb7cb98fe5208bcdf5a3a7"},"schema_version":"1.0","source":{"id":"1903.06638","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1903.06638","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"arxiv_version","alias_value":"1903.06638v1","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1903.06638","created_at":"2026-05-17T23:51:10Z"},{"alias_kind":"pith_short_12","alias_value":"HLGTIBNH5E3A","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_16","alias_value":"HLGTIBNH5E3A5OFT","created_at":"2026-05-18T12:33:18Z"},{"alias_kind":"pith_short_8","alias_value":"HLGTIBNH","created_at":"2026-05-18T12:33:18Z"}],"graph_snapshots":[{"event_id":"sha256:654efc0bcf61def961652ef9965a8c0ba9b9090fb906db9d940315e83856bed5","target":"graph","created_at":"2026-05-17T23:51:10Z","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":"Recent work has identified that classification models implemented as neural networks are vulnerable to data-poisoning and Trojan attacks at training time. In this work, we show that these training-time vulnerabilities extend to deep reinforcement learning (DRL) agents and can be exploited by an adversary with access to the training process. In particular, we focus on Trojan attacks that augment the function of reinforcement learning policies with hidden behaviors. We demonstrate that such attacks can be implemented through minuscule data poisoning (as little as 0.025% of the training data) and","authors_text":"Kacper Wardega, Panagiota Kiourti, Susmit Jha, Wenchao Li","cross_cats":["cs.LG","stat.ML"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-03-01T04:17:32Z","title":"TrojDRL: Trojan Attacks on Deep Reinforcement Learning Agents"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1903.06638","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:a00d5872087fd4066d8a46275fb5c423c022a189f8fed1acd572b0ee6b8c6f33","target":"record","created_at":"2026-05-17T23:51:10Z","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":"46025c5aad3af83f8059a46fe745eff79c1bced11dbead972962163710d1fed9","cross_cats_sorted":["cs.LG","stat.ML"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2019-03-01T04:17:32Z","title_canon_sha256":"e978e45e85679d537502a675ae7933356a105ab626bb7cb98fe5208bcdf5a3a7"},"schema_version":"1.0","source":{"id":"1903.06638","kind":"arxiv","version":1}},"canonical_sha256":"3acd3405a7e9360eb8b33f121afb9d0fea03beef93db0c50575f4fba1a6f1e5f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"3acd3405a7e9360eb8b33f121afb9d0fea03beef93db0c50575f4fba1a6f1e5f","first_computed_at":"2026-05-17T23:51:10.263063Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-05-17T23:51:10.263063Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"0hr4ijDX+6Hbsil8ZAVig0y/hBVve7D/GlEQrrr+9ScbOvW01dyvpvnnTCvoBFilfWTV1iDAOQSmwWWQ2mVgDw==","signature_status":"signed_v1","signed_at":"2026-05-17T23:51:10.263664Z","signed_message":"canonical_sha256_bytes"},"source_id":"1903.06638","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:a00d5872087fd4066d8a46275fb5c423c022a189f8fed1acd572b0ee6b8c6f33","sha256:654efc0bcf61def961652ef9965a8c0ba9b9090fb906db9d940315e83856bed5"],"state_sha256":"3bcff6266def7c2aafeb9cba432bf89f0ffadf56ef7d915548772e3812c218d5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"2SdyLsyT7EhSHqu7mizhVYRhKU8ucqi8FFBcHYvBbiH0qxqyGItTN43bs3VkFXpPNlFj0mlJqji6kmdUM+AVCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-05-20T15:28:10.373475Z","bundle_sha256":"95a1be861a2433464d5c0e93a259b297e8c3c94f2e87ba0d4d78de1b36f8ce14"}}