{"id":"W3095315034","doi":"10.1109/tsg.2020.3034745","title":"Countering FDI Attacks on DERs Coordinated Control System Using FMI-Compatible Cosimulation","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Smart Grid","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hydro-Québec; Polytechnique Montréal","funders":"Mitacs","keywords":"SCADA; Benchmark (surveying); Embedded system; Co-simulation; Controller (irrigation); Engineering; Photovoltaic system; Control system; Cyber-physical system; Distributed control system; Control engineering; Computer science; Electrical engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00009929762,0.0002698269,0.0003135989,0.0001410337,0.000292704,0.00007017054,0.0001572914,0.0001370415,0.00004604306],"category_scores_gemma":[0.000004161247,0.0002804598,0.0001281355,0.0003890135,0.00004704277,0.0002186547,8.658119e-7,0.0003963209,0.0001532876],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002305001,"about_ca_system_score_gemma":0.00002480821,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005353747,"about_ca_topic_score_gemma":0.0000257699,"domain_scores_codex":[0.9986737,0.00005841551,0.0003450016,0.0003028465,0.0002788956,0.0003411199],"domain_scores_gemma":[0.9993678,0.0001238776,0.00004660034,0.0002133336,0.00006036767,0.0001880374],"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":[0.0001152441,0.00003641576,0.00009300777,0.0001593957,0.00007499362,0.00001044967,0.0003481749,0.9881197,0.01040239,0.00001255655,0.0003731374,0.0002545351],"study_design_scores_gemma":[0.001137078,0.0001419974,0.0001533611,0.000191829,0.00006444815,0.00001619828,0.0002085334,0.9700779,0.02636206,7.604461e-7,0.001348694,0.0002971803],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3598877,0.00003823024,0.6349335,0.0001162234,0.003479024,0.0003541917,0.00008604452,0.0007339098,0.0003710805],"genre_scores_gemma":[0.9991925,0.00001387686,0.0001280705,0.0002521953,0.0003209308,0.0000234167,0.000006081786,0.00005336218,0.0000095875],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6393047,"threshold_uncertainty_score":0.9999648,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02282019014510795,"score_gpt":0.2226557870255498,"score_spread":0.1998355968804418,"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."}}