{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2016:KMNHFV37TWHXFOYH5XIZE4A3WE","short_pith_number":"pith:KMNHFV37","schema_version":"1.0","canonical_sha256":"531a72d77f9d8f72bb07edd192701bb12855efa719ff913af4158be3e7d7dc40","source":{"kind":"arxiv","id":"1604.07549","version":2},"attestation_state":"computed","paper":{"title":"Towards a Unified Resilience Analysis: State Estimation against Integrity Attacks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Duo Han, Lihua Xie, Yilin Mo","submitted_at":"2016-04-26T07:08:43Z","abstract_excerpt":"We consider the problem of resilient state estimation in the presence of integrity attacks. There are m sensors monitoring the state and p of them are under attack. The sensory data collected by the compromised sensors can be manipulated arbitrarily by the attacker. The classical estimators such as the least squares estimator may not provide a reliable estimate under the so-called (p,m)-sparse attack. In this work, we are not restricting our efforts in studying whether any specific estimator is resilient to the attack or not, but instead we aim to present the generic sufficient and necessary c"},"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":"1604.07549","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.IT","submitted_at":"2016-04-26T07:08:43Z","cross_cats_sorted":["math.IT"],"title_canon_sha256":"74cc10de5637ccfa240a9e1c68efb84b2271931ee5c477d5f6004e02562736b1","abstract_canon_sha256":"79a8675e718965a9aa8ae17fddaf0a1faef11994bcf70829e380f041267068ef"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T01:15:48.662377Z","signature_b64":"4TL5fW6jlEd/shckqywUlqiun4TWaAp4WPLGnyzTP3gX+0xczyLzj2CcAZlTR5wdWpAipbjU60xw2pAGERC0AQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"531a72d77f9d8f72bb07edd192701bb12855efa719ff913af4158be3e7d7dc40","last_reissued_at":"2026-05-18T01:15:48.661708Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T01:15:48.661708Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Towards a Unified Resilience Analysis: State Estimation against Integrity Attacks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["math.IT"],"primary_cat":"cs.IT","authors_text":"Duo Han, Lihua Xie, Yilin Mo","submitted_at":"2016-04-26T07:08:43Z","abstract_excerpt":"We consider the problem of resilient state estimation in the presence of integrity attacks. There are m sensors monitoring the state and p of them are under attack. The sensory data collected by the compromised sensors can be manipulated arbitrarily by the attacker. The classical estimators such as the least squares estimator may not provide a reliable estimate under the so-called (p,m)-sparse attack. In this work, we are not restricting our efforts in studying whether any specific estimator is resilient to the attack or not, but instead we aim to present the generic sufficient and necessary c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1604.07549","kind":"arxiv","version":2},"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"},"aliases":[{"alias_kind":"arxiv","alias_value":"1604.07549","created_at":"2026-05-18T01:15:48.661808+00:00"},{"alias_kind":"arxiv_version","alias_value":"1604.07549v2","created_at":"2026-05-18T01:15:48.661808+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1604.07549","created_at":"2026-05-18T01:15:48.661808+00:00"},{"alias_kind":"pith_short_12","alias_value":"KMNHFV37TWHX","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_16","alias_value":"KMNHFV37TWHXFOYH","created_at":"2026-05-18T12:30:25.849896+00:00"},{"alias_kind":"pith_short_8","alias_value":"KMNHFV37","created_at":"2026-05-18T12:30:25.849896+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/KMNHFV37TWHXFOYH5XIZE4A3WE","json":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE.json","graph_json":"https://pith.science/api/pith-number/KMNHFV37TWHXFOYH5XIZE4A3WE/graph.json","events_json":"https://pith.science/api/pith-number/KMNHFV37TWHXFOYH5XIZE4A3WE/events.json","paper":"https://pith.science/paper/KMNHFV37"},"agent_actions":{"view_html":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE","download_json":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE.json","view_paper":"https://pith.science/paper/KMNHFV37","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1604.07549&json=true","fetch_graph":"https://pith.science/api/pith-number/KMNHFV37TWHXFOYH5XIZE4A3WE/graph.json","fetch_events":"https://pith.science/api/pith-number/KMNHFV37TWHXFOYH5XIZE4A3WE/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE/action/timestamp_anchor","attest_storage":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE/action/storage_attestation","attest_author":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE/action/author_attestation","sign_citation":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE/action/citation_signature","submit_replication":"https://pith.science/pith/KMNHFV37TWHXFOYH5XIZE4A3WE/action/replication_record"}},"created_at":"2026-05-18T01:15:48.661808+00:00","updated_at":"2026-05-18T01:15:48.661808+00:00"}