{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2021:VK2PEP62OCYWXHMY4S5D6VQC2P","short_pith_number":"pith:VK2PEP62","canonical_record":{"source":{"id":"2106.08361","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-15T18:15:26Z","cross_cats_sorted":["cs.CR","q-fin.ST"],"title_canon_sha256":"fdbe152dea3bcbfb0d1f8ee620fa65c3ce224d68965773b474cb60971dab941e","abstract_canon_sha256":"d347333d47133837d5bf0031e3532bba0941432e70e4b8cf03a4e65d80644394"},"schema_version":"1.0"},"canonical_sha256":"aab4f23fda70b16b9d98e4ba3f5602d3ed96c06c95f02aabd60dc191811614fc","source":{"kind":"arxiv","id":"2106.08361","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.08361","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"arxiv_version","alias_value":"2106.08361v1","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08361","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_12","alias_value":"VK2PEP62OCYW","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_16","alias_value":"VK2PEP62OCYWXHMY","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_8","alias_value":"VK2PEP62","created_at":"2026-07-05T02:49:57Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2021:VK2PEP62OCYWXHMY4S5D6VQC2P","target":"record","payload":{"canonical_record":{"source":{"id":"2106.08361","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-15T18:15:26Z","cross_cats_sorted":["cs.CR","q-fin.ST"],"title_canon_sha256":"fdbe152dea3bcbfb0d1f8ee620fa65c3ce224d68965773b474cb60971dab941e","abstract_canon_sha256":"d347333d47133837d5bf0031e3532bba0941432e70e4b8cf03a4e65d80644394"},"schema_version":"1.0"},"canonical_sha256":"aab4f23fda70b16b9d98e4ba3f5602d3ed96c06c95f02aabd60dc191811614fc","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T02:49:57.029682Z","signature_b64":"1A9DDaTmHw0zsSowW/A4bJPaj9YSdkLfcNFINtL0ggmazSsmSutv/QqGRm47O6ffoRANvL5clMijkoOydHoLAg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"aab4f23fda70b16b9d98e4ba3f5602d3ed96c06c95f02aabd60dc191811614fc","last_reissued_at":"2026-07-05T02:49:57.029164Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T02:49:57.029164Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2106.08361","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":"2026-07-05T02:49:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Du7VTuskauTLAbCga1zn+t67DieUTstdtMr08s7Kz575dpEGh4oqnVlxLEJ9zgp7I+0K1hs0yAtDyCZQrEusAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:45:58.602521Z"},"content_sha256":"42e2c05a7626bd42b01ec46aa86f21d4d05762d7407689ec3061db561fe345ea","schema_version":"1.0","event_id":"sha256:42e2c05a7626bd42b01ec46aa86f21d4d05762d7407689ec3061db561fe345ea"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2021:VK2PEP62OCYWXHMY4S5D6VQC2P","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Adversarial Attacks on Deep Models for Financial Transaction Records","license":"http://creativecommons.org/publicdomain/zero/1.0/","headline":"","cross_cats":["cs.CR","q-fin.ST"],"primary_cat":"cs.LG","authors_text":"Alexey Zaytsev, Dmitry Babaev, Elizaveta Kovtun, Evgeny Burnaev, Gleb Gusev, Ivan Fursov, Ivan Kireev, Matvey Morozov, Nina Kaploukhaya, Rodrigo Rivera-Castro","submitted_at":"2021-06-15T18:15:26Z","abstract_excerpt":"Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in the NLP community, posing a challenge due to their tremendous number of parameters and limited robustness. In particular, deep-learning models are vulnerable to adversarial attacks: a little change in the input harms the model's output.\n  In this work, we examine adversarial attacks on transaction records data and defences from these attacks. The transaction records data have a different structure than the canonical "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08361","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/2106.08361/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":"2026-07-05T02:49:57Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"M209DXRbaj9eYjmzvHrHMCtv22vV9sWnnVG/5/iYwGjo8hk09sg8ZTbjiK1KbbzS9oDZqOEuJfKF0ZgGKNxTDA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-01T08:45:58.603014Z"},"content_sha256":"79071ecd06d6a5ce4c37fb0d47e456f31218f1c74b53ed337b4833a012849f64","schema_version":"1.0","event_id":"sha256:79071ecd06d6a5ce4c37fb0d47e456f31218f1c74b53ed337b4833a012849f64"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/bundle.json","state_url":"https://pith.science/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/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":"2026-08-01T08:45:58Z","links":{"resolver":"https://pith.science/pith/VK2PEP62OCYWXHMY4S5D6VQC2P","bundle":"https://pith.science/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/bundle.json","state":"https://pith.science/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VK2PEP62OCYWXHMY4S5D6VQC2P/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2021:VK2PEP62OCYWXHMY4S5D6VQC2P","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":"d347333d47133837d5bf0031e3532bba0941432e70e4b8cf03a4e65d80644394","cross_cats_sorted":["cs.CR","q-fin.ST"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-15T18:15:26Z","title_canon_sha256":"fdbe152dea3bcbfb0d1f8ee620fa65c3ce224d68965773b474cb60971dab941e"},"schema_version":"1.0","source":{"id":"2106.08361","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2106.08361","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"arxiv_version","alias_value":"2106.08361v1","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2106.08361","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_12","alias_value":"VK2PEP62OCYW","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_16","alias_value":"VK2PEP62OCYWXHMY","created_at":"2026-07-05T02:49:57Z"},{"alias_kind":"pith_short_8","alias_value":"VK2PEP62","created_at":"2026-07-05T02:49:57Z"}],"graph_snapshots":[{"event_id":"sha256:79071ecd06d6a5ce4c37fb0d47e456f31218f1c74b53ed337b4833a012849f64","target":"graph","created_at":"2026-07-05T02:49:57Z","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/2106.08361/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in the NLP community, posing a challenge due to their tremendous number of parameters and limited robustness. In particular, deep-learning models are vulnerable to adversarial attacks: a little change in the input harms the model's output.\n  In this work, we examine adversarial attacks on transaction records data and defences from these attacks. The transaction records data have a different structure than the canonical ","authors_text":"Alexey Zaytsev, Dmitry Babaev, Elizaveta Kovtun, Evgeny Burnaev, Gleb Gusev, Ivan Fursov, Ivan Kireev, Matvey Morozov, Nina Kaploukhaya, Rodrigo Rivera-Castro","cross_cats":["cs.CR","q-fin.ST"],"headline":"","license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-15T18:15:26Z","title":"Adversarial Attacks on Deep Models for Financial Transaction Records"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2106.08361","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":"sha256:42e2c05a7626bd42b01ec46aa86f21d4d05762d7407689ec3061db561fe345ea","target":"record","created_at":"2026-07-05T02:49:57Z","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":"d347333d47133837d5bf0031e3532bba0941432e70e4b8cf03a4e65d80644394","cross_cats_sorted":["cs.CR","q-fin.ST"],"license":"http://creativecommons.org/publicdomain/zero/1.0/","primary_cat":"cs.LG","submitted_at":"2021-06-15T18:15:26Z","title_canon_sha256":"fdbe152dea3bcbfb0d1f8ee620fa65c3ce224d68965773b474cb60971dab941e"},"schema_version":"1.0","source":{"id":"2106.08361","kind":"arxiv","version":1}},"canonical_sha256":"aab4f23fda70b16b9d98e4ba3f5602d3ed96c06c95f02aabd60dc191811614fc","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"aab4f23fda70b16b9d98e4ba3f5602d3ed96c06c95f02aabd60dc191811614fc","first_computed_at":"2026-07-05T02:49:57.029164Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T02:49:57.029164Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1A9DDaTmHw0zsSowW/A4bJPaj9YSdkLfcNFINtL0ggmazSsmSutv/QqGRm47O6ffoRANvL5clMijkoOydHoLAg==","signature_status":"signed_v1","signed_at":"2026-07-05T02:49:57.029682Z","signed_message":"canonical_sha256_bytes"},"source_id":"2106.08361","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:42e2c05a7626bd42b01ec46aa86f21d4d05762d7407689ec3061db561fe345ea","sha256:79071ecd06d6a5ce4c37fb0d47e456f31218f1c74b53ed337b4833a012849f64"],"state_sha256":"d0a311a547a4a69a0fbd47fdbff96fb6e01836f8db4c14fabaa09c5ae8383cf0"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"XPJDt1F55NzhZImCDHKtV3YdOpHHpeqLZI+/p9RFoRezNPLGYAv7WNP1t89igC9PNo2qmd8V6qKS1Jhe0CXgAA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-01T08:45:58.607527Z","bundle_sha256":"d60fb5d0d14833697d0c5f32e0585bab42cabb5b23d4bee83dfc77707a741f94"}}