{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:Y5B5GSIU3V36CBIEASA5YRMKTD","short_pith_number":"pith:Y5B5GSIU","canonical_record":{"source":{"id":"2301.04299","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-11T04:25:00Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"0c709415604fb81e45a00e27542c2d6da3539dbab8b2466d2d79aff2ee443351","abstract_canon_sha256":"86192f3b236a3823855058ce9d5467b45456ee73892a62915a154deb1e79fa7b"},"schema_version":"1.0"},"canonical_sha256":"c743d34914dd77e105040481dc458a98d329b0bedf38a01aabaae6d56d3e8fe8","source":{"kind":"arxiv","id":"2301.04299","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.04299","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"arxiv_version","alias_value":"2301.04299v1","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.04299","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_12","alias_value":"Y5B5GSIU3V36","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_16","alias_value":"Y5B5GSIU3V36CBIE","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_8","alias_value":"Y5B5GSIU","created_at":"2026-07-05T05:32:14Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:Y5B5GSIU3V36CBIEASA5YRMKTD","target":"record","payload":{"canonical_record":{"source":{"id":"2301.04299","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-11T04:25:00Z","cross_cats_sorted":["cs.AI","cs.CR"],"title_canon_sha256":"0c709415604fb81e45a00e27542c2d6da3539dbab8b2466d2d79aff2ee443351","abstract_canon_sha256":"86192f3b236a3823855058ce9d5467b45456ee73892a62915a154deb1e79fa7b"},"schema_version":"1.0"},"canonical_sha256":"c743d34914dd77e105040481dc458a98d329b0bedf38a01aabaae6d56d3e8fe8","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:32:14.703182Z","signature_b64":"abiT77ya4i7CuzLxihc6QHCh3DvpOAKu6lprI/FpwqVMWkRfJbzAY2IwxBT0ib6madCKdEd4DlO7kXM5ByHkCw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c743d34914dd77e105040481dc458a98d329b0bedf38a01aabaae6d56d3e8fe8","last_reissued_at":"2026-07-05T05:32:14.702714Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:32:14.702714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2301.04299","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":"2026-07-05T05:32:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"P2eDVe/3InzPypEkItv66QUFHrrQw2N/onON805anpxbmtSe3EHeWSfXzqTar/V1LgS1zt16c8FryLDpRDCVDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:32:34.119912Z"},"content_sha256":"72917357972a20f8be1f47313b44ce7aa97a2155c0b3659d5117594ef65f5cdb","schema_version":"1.0","event_id":"sha256:72917357972a20f8be1f47313b44ce7aa97a2155c0b3659d5117594ef65f5cdb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:Y5B5GSIU3V36CBIEASA5YRMKTD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","headline":"","cross_cats":["cs.AI","cs.CR"],"primary_cat":"cs.LG","authors_text":"Claudia Szabo, Junae Kim, Maxwell Standen","submitted_at":"2023-01-11T04:25:00Z","abstract_excerpt":"Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications. We have conducted a survey into the use of execution-time AML attacks against MARL and the defences against those attacks. We surveyed related work in the application of AML in Deep Reinforcement Learning (DRL) and Multi-Agent Learning (MAL) to inform our analysis of AML for MARL. We propose a novel perspective to understand the manner of perpetrating an AML attack, by defining Attack Vectors. We develop two new fram"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.04299","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2301.04299/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":"2026-07-05T05:32:14Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"g/N6mE3cIRe2UUXyCY9OFczv3eEc4MhLeGgrUcf0TdUjoqE0UkZpaSW157bFp2s47S98+iWRKJhl/wKOz6O5BA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-09T19:32:34.120431Z"},"content_sha256":"0abf4fcbac8addbeb58fa6bab05fb71016cd5fead8a4ec111c0219e679b33270","schema_version":"1.0","event_id":"sha256:0abf4fcbac8addbeb58fa6bab05fb71016cd5fead8a4ec111c0219e679b33270"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/bundle.json","state_url":"https://pith.science/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/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":"2026-08-09T19:32:34Z","links":{"resolver":"https://pith.science/pith/Y5B5GSIU3V36CBIEASA5YRMKTD","bundle":"https://pith.science/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/bundle.json","state":"https://pith.science/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/Y5B5GSIU3V36CBIEASA5YRMKTD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:Y5B5GSIU3V36CBIEASA5YRMKTD","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":"86192f3b236a3823855058ce9d5467b45456ee73892a62915a154deb1e79fa7b","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-11T04:25:00Z","title_canon_sha256":"0c709415604fb81e45a00e27542c2d6da3539dbab8b2466d2d79aff2ee443351"},"schema_version":"1.0","source":{"id":"2301.04299","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2301.04299","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"arxiv_version","alias_value":"2301.04299v1","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2301.04299","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_12","alias_value":"Y5B5GSIU3V36","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_16","alias_value":"Y5B5GSIU3V36CBIE","created_at":"2026-07-05T05:32:14Z"},{"alias_kind":"pith_short_8","alias_value":"Y5B5GSIU","created_at":"2026-07-05T05:32:14Z"}],"graph_snapshots":[{"event_id":"sha256:0abf4fcbac8addbeb58fa6bab05fb71016cd5fead8a4ec111c0219e679b33270","target":"graph","created_at":"2026-07-05T05:32:14Z","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/2301.04299/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Multi-Agent Reinforcement Learning (MARL) is vulnerable to Adversarial Machine Learning (AML) attacks and needs adequate defences before it can be used in real world applications. We have conducted a survey into the use of execution-time AML attacks against MARL and the defences against those attacks. We surveyed related work in the application of AML in Deep Reinforcement Learning (DRL) and Multi-Agent Learning (MAL) to inform our analysis of AML for MARL. We propose a novel perspective to understand the manner of perpetrating an AML attack, by defining Attack Vectors. We develop two new fram","authors_text":"Claudia Szabo, Junae Kim, Maxwell Standen","cross_cats":["cs.AI","cs.CR"],"headline":"","license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-11T04:25:00Z","title":"SoK: Adversarial Machine Learning Attacks and Defences in Multi-Agent Reinforcement Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2301.04299","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":"sha256:72917357972a20f8be1f47313b44ce7aa97a2155c0b3659d5117594ef65f5cdb","target":"record","created_at":"2026-07-05T05:32:14Z","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":"86192f3b236a3823855058ce9d5467b45456ee73892a62915a154deb1e79fa7b","cross_cats_sorted":["cs.AI","cs.CR"],"license":"http://creativecommons.org/licenses/by-nc-sa/4.0/","primary_cat":"cs.LG","submitted_at":"2023-01-11T04:25:00Z","title_canon_sha256":"0c709415604fb81e45a00e27542c2d6da3539dbab8b2466d2d79aff2ee443351"},"schema_version":"1.0","source":{"id":"2301.04299","kind":"arxiv","version":1}},"canonical_sha256":"c743d34914dd77e105040481dc458a98d329b0bedf38a01aabaae6d56d3e8fe8","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"c743d34914dd77e105040481dc458a98d329b0bedf38a01aabaae6d56d3e8fe8","first_computed_at":"2026-07-05T05:32:14.702714Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:32:14.702714Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"abiT77ya4i7CuzLxihc6QHCh3DvpOAKu6lprI/FpwqVMWkRfJbzAY2IwxBT0ib6madCKdEd4DlO7kXM5ByHkCw==","signature_status":"signed_v1","signed_at":"2026-07-05T05:32:14.703182Z","signed_message":"canonical_sha256_bytes"},"source_id":"2301.04299","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:72917357972a20f8be1f47313b44ce7aa97a2155c0b3659d5117594ef65f5cdb","sha256:0abf4fcbac8addbeb58fa6bab05fb71016cd5fead8a4ec111c0219e679b33270"],"state_sha256":"1b456fe89764f2143bdc790115520c8e53d24d2f9ce109042a0d0d4b55cd72b5"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IvYU3JHFyNZlvdjxEqRy3Qw40GFZRWte2XfkUw1aLGCodvLDSOSzxhm40T9DdGGL2gvLtcCtkAQiLuReiEWfAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-09T19:32:34.127486Z","bundle_sha256":"6bc85d2849f8408f3dfe528412c03f850f0440e256b8d3ed35faff8b8171785e"}}