{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2025:XTZ2F6TM2M6S6MEQ3B44W2VX2C","short_pith_number":"pith:XTZ2F6TM","schema_version":"1.0","canonical_sha256":"bcf3a2fa6cd33d2f3090d879cb6ab7d08dc15286cba56f33c42e8b5878df09ce","source":{"kind":"arxiv","id":"2506.06572","version":3},"attestation_state":"computed","paper":{"title":"Cyber Security of Sensor Systems for State Sequence Estimation: A Machine Learning Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.CR","authors_text":"Brian M. Sadler, Ramesh Bharadwaj, Rick S. Blum, Xubin Fang","submitted_at":"2025-06-06T22:51:44Z","abstract_excerpt":"Due to possible devastating consequences, counteracting sensor data attacks is an extremely impor- tant topic, which has not seen sufficient study. To the best of our knowledge, this paper develops the first meth- ods that accurately identify/eliminate only the problem- atic attacked sensor data presented to a sequence es- timation/regression algorithm under any attack from our attack model. The approach does not assume a known form for the statistical model of the sensor data, allow- ing data-driven and machine learning sequence estima- tion/regression algorithms to be protected. A simple pro"},"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":"2506.06572","kind":"arxiv","version":3},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.CR","submitted_at":"2025-06-06T22:51:44Z","cross_cats_sorted":["eess.SP"],"title_canon_sha256":"6f47843bcd4b8f7f2f3c4a026dba74bc3d9b7f400c022c528e7f3dda10a3137f","abstract_canon_sha256":"76d533eeaf07bf64f28526d979612febf3014d6ddc7aac95d901d1ed3830a226"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-02T01:03:31.953616Z","signature_b64":"TaMr+ixLWXVzXw2PoeZhrHKmRG5D9NE+iylnMIxC3wXwAIGxHwUfZ7ZzIaZv/FuMqu38RxaxPzBqdJ+UYeiwDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"bcf3a2fa6cd33d2f3090d879cb6ab7d08dc15286cba56f33c42e8b5878df09ce","last_reissued_at":"2026-06-02T01:03:31.953031Z","signature_status":"signed_v1","first_computed_at":"2026-06-02T01:03:31.953031Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Cyber Security of Sensor Systems for State Sequence Estimation: A Machine Learning Approach","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["eess.SP"],"primary_cat":"cs.CR","authors_text":"Brian M. Sadler, Ramesh Bharadwaj, Rick S. Blum, Xubin Fang","submitted_at":"2025-06-06T22:51:44Z","abstract_excerpt":"Due to possible devastating consequences, counteracting sensor data attacks is an extremely impor- tant topic, which has not seen sufficient study. To the best of our knowledge, this paper develops the first meth- ods that accurately identify/eliminate only the problem- atic attacked sensor data presented to a sequence es- timation/regression algorithm under any attack from our attack model. The approach does not assume a known form for the statistical model of the sensor data, allow- ing data-driven and machine learning sequence estima- tion/regression algorithms to be protected. A simple pro"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2506.06572","kind":"arxiv","version":3},"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/2506.06572/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":"2506.06572","created_at":"2026-06-02T01:03:31.953141+00:00"},{"alias_kind":"arxiv_version","alias_value":"2506.06572v3","created_at":"2026-06-02T01:03:31.953141+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2506.06572","created_at":"2026-06-02T01:03:31.953141+00:00"},{"alias_kind":"pith_short_12","alias_value":"XTZ2F6TM2M6S","created_at":"2026-06-02T01:03:31.953141+00:00"},{"alias_kind":"pith_short_16","alias_value":"XTZ2F6TM2M6S6MEQ","created_at":"2026-06-02T01:03:31.953141+00:00"},{"alias_kind":"pith_short_8","alias_value":"XTZ2F6TM","created_at":"2026-06-02T01:03:31.953141+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/XTZ2F6TM2M6S6MEQ3B44W2VX2C","json":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C.json","graph_json":"https://pith.science/api/pith-number/XTZ2F6TM2M6S6MEQ3B44W2VX2C/graph.json","events_json":"https://pith.science/api/pith-number/XTZ2F6TM2M6S6MEQ3B44W2VX2C/events.json","paper":"https://pith.science/paper/XTZ2F6TM"},"agent_actions":{"view_html":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C","download_json":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C.json","view_paper":"https://pith.science/paper/XTZ2F6TM","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2506.06572&json=true","fetch_graph":"https://pith.science/api/pith-number/XTZ2F6TM2M6S6MEQ3B44W2VX2C/graph.json","fetch_events":"https://pith.science/api/pith-number/XTZ2F6TM2M6S6MEQ3B44W2VX2C/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C/action/timestamp_anchor","attest_storage":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C/action/storage_attestation","attest_author":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C/action/author_attestation","sign_citation":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C/action/citation_signature","submit_replication":"https://pith.science/pith/XTZ2F6TM2M6S6MEQ3B44W2VX2C/action/replication_record"}},"created_at":"2026-06-02T01:03:31.953141+00:00","updated_at":"2026-06-02T01:03:31.953141+00:00"}