{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2024:IAPQWDM4LETGN7PHVPMILRTGOD","short_pith_number":"pith:IAPQWDM4","schema_version":"1.0","canonical_sha256":"401f0b0d9c592666fde7abd885c66670d4640a1ef32bdde4d3240836e3941bf1","source":{"kind":"arxiv","id":"2407.18448","version":2},"attestation_state":"computed","paper":{"title":"Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Fred Y. Hadaegh, Hiroyasu Tsukamoto, Joudi Hajar, Soon-Jo Chung","submitted_at":"2024-07-26T01:03:56Z","abstract_excerpt":"Modern control designs in robotics, aerospace, and cyber-physical systems rely heavily on real-world data obtained through system outputs. However, these outputs can be compromised by system faults and malicious attacks, distorting critical system information needed for secure and reliable operation. In this paper, we introduce a novel regret-optimal control framework for designing controllers that make a linear system robust against stealthy attacks, including both sensor and actuator attacks. Specifically, we present (a) a convex optimization-based system metric to quantify the regret under "},"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":"2407.18448","kind":"arxiv","version":2},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"eess.SY","submitted_at":"2024-07-26T01:03:56Z","cross_cats_sorted":["cs.SY"],"title_canon_sha256":"8d0c92752d88242542cdf684bd2a0f3ad177450d68b7769a5e8715b30af9d9eb","abstract_canon_sha256":"3d9adeca0d8b90dfa45051dfd33197908cc765e98fa2f80aff6788c8f5931a5d"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:07:01.711620Z","signature_b64":"MFez452+k4XVY0tw4pBc6bfH4nqUuPP29J0YG1stBn8S9Xa0LlLLhV8/Y1OyMMJ+L6aevBu+tdiuBniyYVidCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"401f0b0d9c592666fde7abd885c66670d4640a1ef32bdde4d3240836e3941bf1","last_reissued_at":"2026-07-05T09:07:01.711149Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:07:01.711149Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Regret-Optimal Defense Against Stealthy Adversaries: A System Level Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.SY"],"primary_cat":"eess.SY","authors_text":"Fred Y. Hadaegh, Hiroyasu Tsukamoto, Joudi Hajar, Soon-Jo Chung","submitted_at":"2024-07-26T01:03:56Z","abstract_excerpt":"Modern control designs in robotics, aerospace, and cyber-physical systems rely heavily on real-world data obtained through system outputs. However, these outputs can be compromised by system faults and malicious attacks, distorting critical system information needed for secure and reliable operation. In this paper, we introduce a novel regret-optimal control framework for designing controllers that make a linear system robust against stealthy attacks, including both sensor and actuator attacks. Specifically, we present (a) a convex optimization-based system metric to quantify the regret under "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2407.18448","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":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2407.18448/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":"2407.18448","created_at":"2026-07-05T09:07:01.711209+00:00"},{"alias_kind":"arxiv_version","alias_value":"2407.18448v2","created_at":"2026-07-05T09:07:01.711209+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2407.18448","created_at":"2026-07-05T09:07:01.711209+00:00"},{"alias_kind":"pith_short_12","alias_value":"IAPQWDM4LETG","created_at":"2026-07-05T09:07:01.711209+00:00"},{"alias_kind":"pith_short_16","alias_value":"IAPQWDM4LETGN7PH","created_at":"2026-07-05T09:07:01.711209+00:00"},{"alias_kind":"pith_short_8","alias_value":"IAPQWDM4","created_at":"2026-07-05T09:07:01.711209+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/IAPQWDM4LETGN7PHVPMILRTGOD","json":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD.json","graph_json":"https://pith.science/api/pith-number/IAPQWDM4LETGN7PHVPMILRTGOD/graph.json","events_json":"https://pith.science/api/pith-number/IAPQWDM4LETGN7PHVPMILRTGOD/events.json","paper":"https://pith.science/paper/IAPQWDM4"},"agent_actions":{"view_html":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD","download_json":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD.json","view_paper":"https://pith.science/paper/IAPQWDM4","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2407.18448&json=true","fetch_graph":"https://pith.science/api/pith-number/IAPQWDM4LETGN7PHVPMILRTGOD/graph.json","fetch_events":"https://pith.science/api/pith-number/IAPQWDM4LETGN7PHVPMILRTGOD/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD/action/timestamp_anchor","attest_storage":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD/action/storage_attestation","attest_author":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD/action/author_attestation","sign_citation":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD/action/citation_signature","submit_replication":"https://pith.science/pith/IAPQWDM4LETGN7PHVPMILRTGOD/action/replication_record"}},"created_at":"2026-07-05T09:07:01.711209+00:00","updated_at":"2026-07-05T09:07:01.711209+00:00"}