{"id":"W3181784683","doi":"10.1109/icps49255.2021.9468197","title":"Optimal Linear FDI Attacks with Side Information: A Comparative Study","year":2021,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; China Scholarship Council","keywords":"Computer science; Covariance; Detector; Convex optimization; Scalar (mathematics); Anomaly (physics); Anomaly detection; Mathematical optimization; State (computer science); Regular polygon; Algorithm; Data mining; Mathematics; Statistics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00003657833,0.00008282079,0.0001135069,0.00002546238,0.00005248057,0.00003970978,0.00006426183,0.00002432949,0.0001289335],"category_scores_gemma":[0.000005068484,0.00006234431,0.00001642679,0.0001904507,0.00002236667,0.0003349879,0.00002427498,0.0001164497,0.0001800098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000133239,"about_ca_system_score_gemma":0.00002620664,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007311748,"about_ca_topic_score_gemma":0.0001155883,"domain_scores_codex":[0.9995427,0.00001228331,0.0001215051,0.00006650307,0.0001380425,0.0001189489],"domain_scores_gemma":[0.9997155,0.0000277124,0.000009637474,0.0001294872,0.00007070696,0.0000469635],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00002408818,0.0001208573,0.003764779,0.00003541118,0.0001083344,0.00006418997,0.01843325,0.9738391,0.00008271822,0.0003153947,0.003008219,0.0002036343],"study_design_scores_gemma":[0.003199496,0.0007899221,0.0412855,0.00007568277,0.00006677619,0.0001913019,0.09059221,0.7519667,0.03477249,0.00001134784,0.07607998,0.0009685779],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9570943,0.00005115924,0.009641644,0.00004439458,0.0001261256,0.0001380648,0.000002572504,0.0001815693,0.03272024],"genre_scores_gemma":[0.9963356,0.000005941972,0.003322221,0.0000547464,0.00005352735,0.00001073912,0.000007894998,0.00000392112,0.000205441],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2218724,"threshold_uncertainty_score":0.2542327,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01469619695957327,"score_gpt":0.2479237259097427,"score_spread":0.2332275289501694,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}