{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:ORKZ7SHIXZLG4JWN7TWOSYCCWJ","short_pith_number":"pith:ORKZ7SHI","canonical_record":{"source":{"id":"2403.10802","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-16T04:29:21Z","cross_cats_sorted":[],"title_canon_sha256":"627786dd0d247876ab447693d84460acb870933fd9338a55bce3f88279cd54c2","abstract_canon_sha256":"4dfa5417ed14e080b8000d72fa60a9a41484a078d9bec72f1bdf550c1c22b7cf"},"schema_version":"1.0"},"canonical_sha256":"74559fc8e8be566e26cdfcece96042b25d6e234be9981bd612b14f3537d0f065","source":{"kind":"arxiv","id":"2403.10802","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.10802","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"arxiv_version","alias_value":"2403.10802v1","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10802","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_12","alias_value":"ORKZ7SHIXZLG","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_16","alias_value":"ORKZ7SHIXZLG4JWN","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_8","alias_value":"ORKZ7SHI","created_at":"2026-07-05T10:49:05Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:ORKZ7SHIXZLG4JWN7TWOSYCCWJ","target":"record","payload":{"canonical_record":{"source":{"id":"2403.10802","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-16T04:29:21Z","cross_cats_sorted":[],"title_canon_sha256":"627786dd0d247876ab447693d84460acb870933fd9338a55bce3f88279cd54c2","abstract_canon_sha256":"4dfa5417ed14e080b8000d72fa60a9a41484a078d9bec72f1bdf550c1c22b7cf"},"schema_version":"1.0"},"canonical_sha256":"74559fc8e8be566e26cdfcece96042b25d6e234be9981bd612b14f3537d0f065","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:49:05.517141Z","signature_b64":"C62q94CBvZqPoKTV78Glqk56vHWyp8PrnI9Q2hVRwE9MI1WWM3cuNKlm99h8Oub2fTtvSHvBeD8GVsU2aiK6DA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"74559fc8e8be566e26cdfcece96042b25d6e234be9981bd612b14f3537d0f065","last_reissued_at":"2026-07-05T10:49:05.516640Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:49:05.516640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2403.10802","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":"2026-07-05T10:49:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"aQgtCU69T5qhGgxnOBbn2kR+2JQjmeLJVe54h1vr+LB29nLx7T0jcmp0OJBWlUpgVb0li6jlpJYiaZwPOWk6AA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:04:26.661933Z"},"content_sha256":"6a58af627bb2d70c93d0c70d4436be8f68a516caaec367b71448fe95a4d9406e","schema_version":"1.0","event_id":"sha256:6a58af627bb2d70c93d0c70d4436be8f68a516caaec367b71448fe95a4d9406e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:ORKZ7SHIXZLG4JWN7TWOSYCCWJ","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Anomaly Detection Based on Isolation Mechanisms: A Survey","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.LG","authors_text":"Hang Zhang, Haolong Xiang, Kai Ming Ting, Yang Cao, Ye Zhu","submitted_at":"2024-03-16T04:29:21Z","abstract_excerpt":"Anomaly detection is a longstanding and active research area that has many applications in domains such as finance, security, and manufacturing. However, the efficiency and performance of anomaly detection algorithms are challenged by the large-scale, high-dimensional, and heterogeneous data that are prevalent in the era of big data. Isolation-based unsupervised anomaly detection is a novel and effective approach for identifying anomalies in data. It relies on the idea that anomalies are few and different from normal instances, and thus can be easily isolated by random partitioning. Isolation-"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10802","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/2403.10802/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":"2026-07-05T10:49:05Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"SuVe+s4fLsLA82ztkGsI0XYCu09h74lW5ZJZl/dyt3TMwUQ1wtQ5WaA0q2nHeg99ylQ1BReg2Y2OEXEGOYGTBg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-13T10:04:26.662427Z"},"content_sha256":"7822a9b220874432a4d863dc89a61e83b91209664261cd32492282af94d738e8","schema_version":"1.0","event_id":"sha256:7822a9b220874432a4d863dc89a61e83b91209664261cd32492282af94d738e8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/bundle.json","state_url":"https://pith.science/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/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":"2026-08-13T10:04:26Z","links":{"resolver":"https://pith.science/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ","bundle":"https://pith.science/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/bundle.json","state":"https://pith.science/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ORKZ7SHIXZLG4JWN7TWOSYCCWJ/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:ORKZ7SHIXZLG4JWN7TWOSYCCWJ","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":"4dfa5417ed14e080b8000d72fa60a9a41484a078d9bec72f1bdf550c1c22b7cf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-16T04:29:21Z","title_canon_sha256":"627786dd0d247876ab447693d84460acb870933fd9338a55bce3f88279cd54c2"},"schema_version":"1.0","source":{"id":"2403.10802","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2403.10802","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"arxiv_version","alias_value":"2403.10802v1","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2403.10802","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_12","alias_value":"ORKZ7SHIXZLG","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_16","alias_value":"ORKZ7SHIXZLG4JWN","created_at":"2026-07-05T10:49:05Z"},{"alias_kind":"pith_short_8","alias_value":"ORKZ7SHI","created_at":"2026-07-05T10:49:05Z"}],"graph_snapshots":[{"event_id":"sha256:7822a9b220874432a4d863dc89a61e83b91209664261cd32492282af94d738e8","target":"graph","created_at":"2026-07-05T10:49:05Z","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"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2403.10802/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Anomaly detection is a longstanding and active research area that has many applications in domains such as finance, security, and manufacturing. However, the efficiency and performance of anomaly detection algorithms are challenged by the large-scale, high-dimensional, and heterogeneous data that are prevalent in the era of big data. Isolation-based unsupervised anomaly detection is a novel and effective approach for identifying anomalies in data. It relies on the idea that anomalies are few and different from normal instances, and thus can be easily isolated by random partitioning. Isolation-","authors_text":"Hang Zhang, Haolong Xiang, Kai Ming Ting, Yang Cao, Ye Zhu","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-16T04:29:21Z","title":"Anomaly Detection Based on Isolation Mechanisms: A Survey"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2403.10802","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":"sha256:6a58af627bb2d70c93d0c70d4436be8f68a516caaec367b71448fe95a4d9406e","target":"record","created_at":"2026-07-05T10:49:05Z","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":"4dfa5417ed14e080b8000d72fa60a9a41484a078d9bec72f1bdf550c1c22b7cf","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2024-03-16T04:29:21Z","title_canon_sha256":"627786dd0d247876ab447693d84460acb870933fd9338a55bce3f88279cd54c2"},"schema_version":"1.0","source":{"id":"2403.10802","kind":"arxiv","version":1}},"canonical_sha256":"74559fc8e8be566e26cdfcece96042b25d6e234be9981bd612b14f3537d0f065","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"74559fc8e8be566e26cdfcece96042b25d6e234be9981bd612b14f3537d0f065","first_computed_at":"2026-07-05T10:49:05.516640Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:49:05.516640Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"C62q94CBvZqPoKTV78Glqk56vHWyp8PrnI9Q2hVRwE9MI1WWM3cuNKlm99h8Oub2fTtvSHvBeD8GVsU2aiK6DA==","signature_status":"signed_v1","signed_at":"2026-07-05T10:49:05.517141Z","signed_message":"canonical_sha256_bytes"},"source_id":"2403.10802","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:6a58af627bb2d70c93d0c70d4436be8f68a516caaec367b71448fe95a4d9406e","sha256:7822a9b220874432a4d863dc89a61e83b91209664261cd32492282af94d738e8"],"state_sha256":"944ec4998721df88c8105f5749b3f8f0912ab2bfbd0a35023e9c01a1ea3539df"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"VGkxFrhONUYOcCjhf96tR7GPsXtHoZBcd2/+1QWxQOqtRgZFQwOwTtKJctAI196oDcUT4ovJYNzfMgIDfd0VBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-13T10:04:26.696422Z","bundle_sha256":"d69ff4e6e11c32a4bc783459fb714aa64ed740c1f4fd23889433154f17eb9bf5"}}