{"id":"W2909120408","doi":"10.1109/epec.2018.8598328","title":"Detection of False Data Injection Attacks in Automatic Generation Control Systems Considering System Nonlinearities","year":2018,"lang":"en","type":"article","venue":"","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Automatic Generation Control; Electric power system; Novelty; Stability (learning theory); Computer science; Control theory (sociology); Power (physics); Control system; Automatic frequency control; Control (management); Engineering; Artificial intelligence; Telecommunications; Machine learning","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000889768,0.0005657395,0.0004691797,0.0006282419,0.0001647561,0.0005204511,0.0003920511,0.0005332187,0.0002554924],"category_scores_gemma":[0.004459977,0.0001608876,0.000224822,0.0001918273,0.0003195614,0.000764462,0.0003953635,0.0005947044,0.0001121332],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003813803,"about_ca_system_score_gemma":0.0002794304,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001909413,"about_ca_topic_score_gemma":0.001640085,"domain_scores_codex":[0.9993278,0.0001765642,0.0000465846,0.0001239147,0.000237594,0.00008760441],"domain_scores_gemma":[0.9974698,0.001198025,0.0005152411,0.0002542916,0.0005050918,0.00005754442],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001633594,0.0002731503,0.04948129,0.0003383039,0.0002757301,0.00196442,0.0004660311,0.4115266,0.1094822,0.002999935,0.001427227,0.4201315],"study_design_scores_gemma":[0.000005616279,0.00009420342,0.004305882,0.000007134625,0.00001645079,0.0001930815,0.00002502587,0.9775562,0.01728349,0.0003683826,0.0001337585,0.00001085507],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5721787,0.0004786281,0.4237545,0.0001859149,0.00008189344,0.00003547896,0.0000645076,0.001635704,0.001584649],"genre_scores_gemma":[0.9906313,0.0000407968,0.009092771,0.00001391341,0.000005647146,0.000004266391,0.00002206296,0.000006500854,0.0001826831],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001909413,"threshold_uncertainty_score":0.004705548,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02697867068529102,"score_gpt":0.2396997837681539,"score_spread":0.2127211130828628,"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."}}