{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2019:T437WH7JKRACWGRUIFT6FVXSHP","short_pith_number":"pith:T437WH7J","schema_version":"1.0","canonical_sha256":"9f37fb1fe954402b1a344167e2d6f23be122904ab30f23e505ad9e1b5960be5a","source":{"kind":"arxiv","id":"1909.01469","version":1},"attestation_state":"computed","paper":{"title":"Generalized chi-squared detector for LTI systems with non-Gaussian noise","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Justin Ruths, Navid Hashemi","submitted_at":"2019-09-03T22:07:15Z","abstract_excerpt":"Previously, we derived exact relationships between the properties of a linear time-invariant control system and properties of an anomaly detector that quantified the impact an attacker can have on the system if that attacker aims to remain stealthy to the detector. A necessary first step in this process is to be able to precisely tune the detector to a desired level of performance (false alarm rate) under normal operation, typically through the selection of a threshold parameter. To-date efforts have only considered Gaussian noises. Here we generalize the approach to tune a chi-squared anomaly"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"1909.01469","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"eess.SY","submitted_at":"2019-09-03T22:07:15Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"4cbc167952cafb46356e0defd054af7c0f9abf00d44de0ac58475e7dbf425e0b","abstract_canon_sha256":"5e9e86d26647d8e3dd07d93fba869496bde5849404c1c29284c482c12a54b9ba"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T00:02:16.630441Z","signature_b64":"PPhVRvPmrmDGN663F0T9f0ICBISqgHrFEc7xsU8DIxB2cwAok4t0LqR9F2IEi/mBMvoh1oBuJJBOxe0adTjhDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"9f37fb1fe954402b1a344167e2d6f23be122904ab30f23e505ad9e1b5960be5a","last_reissued_at":"2026-07-05T00:02:16.630051Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T00:02:16.630051Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Generalized chi-squared detector for LTI systems with non-Gaussian noise","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Justin Ruths, Navid Hashemi","submitted_at":"2019-09-03T22:07:15Z","abstract_excerpt":"Previously, we derived exact relationships between the properties of a linear time-invariant control system and properties of an anomaly detector that quantified the impact an attacker can have on the system if that attacker aims to remain stealthy to the detector. A necessary first step in this process is to be able to precisely tune the detector to a desired level of performance (false alarm rate) under normal operation, typically through the selection of a threshold parameter. To-date efforts have only considered Gaussian noises. Here we generalize the approach to tune a chi-squared anomaly"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1909.01469","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/1909.01469/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1909.01469","created_at":"2026-07-05T00:02:16.630107+00:00"},{"alias_kind":"arxiv_version","alias_value":"1909.01469v1","created_at":"2026-07-05T00:02:16.630107+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1909.01469","created_at":"2026-07-05T00:02:16.630107+00:00"},{"alias_kind":"pith_short_12","alias_value":"T437WH7JKRAC","created_at":"2026-07-05T00:02:16.630107+00:00"},{"alias_kind":"pith_short_16","alias_value":"T437WH7JKRACWGRU","created_at":"2026-07-05T00:02:16.630107+00:00"},{"alias_kind":"pith_short_8","alias_value":"T437WH7J","created_at":"2026-07-05T00:02:16.630107+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP","json":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP.json","graph_json":"https://pith.science/api/pith-number/T437WH7JKRACWGRUIFT6FVXSHP/graph.json","events_json":"https://pith.science/api/pith-number/T437WH7JKRACWGRUIFT6FVXSHP/events.json","paper":"https://pith.science/paper/T437WH7J"},"agent_actions":{"view_html":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP","download_json":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP.json","view_paper":"https://pith.science/paper/T437WH7J","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1909.01469&json=true","fetch_graph":"https://pith.science/api/pith-number/T437WH7JKRACWGRUIFT6FVXSHP/graph.json","fetch_events":"https://pith.science/api/pith-number/T437WH7JKRACWGRUIFT6FVXSHP/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP/action/timestamp_anchor","attest_storage":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP/action/storage_attestation","attest_author":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP/action/author_attestation","sign_citation":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP/action/citation_signature","submit_replication":"https://pith.science/pith/T437WH7JKRACWGRUIFT6FVXSHP/action/replication_record"}},"created_at":"2026-07-05T00:02:16.630107+00:00","updated_at":"2026-07-05T00:02:16.630107+00:00"}