{"id":"W3082770156","doi":"10.1109/access.2020.3020891","title":"Model-Based Secure Load Frequency Control of Smart Grids Against Data Integrity Attack","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Beijing Nova Program; Beijing Municipal Commission of Education; National Natural Science Foundation of China","keywords":"Computer science; SCADA; Cyber-physical system; Smart grid; Electric power system; Data integrity; Dynamic demand; Robustness (evolution); Overhead (engineering); Real-time computing; Power (physics); Engineering; Computer security","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":[0.000353658,0.000405355,0.0005229104,0.000410746,0.0003795148,0.0007530407,0.0006372286,0.0004476238,0.001454516],"category_scores_gemma":[0.001356455,0.0001494224,0.0003347611,0.0002542878,0.0005380366,0.001398762,0.0007055326,0.0004935462,0.0003843826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004496687,"about_ca_system_score_gemma":0.0005619742,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009726788,"about_ca_topic_score_gemma":0.0007859081,"domain_scores_codex":[0.9993782,0.00009344929,0.00003329985,0.0001283659,0.0002974702,0.00006907841],"domain_scores_gemma":[0.9994673,0.0001069769,0.0001184214,0.0001809123,0.0001054306,0.00002090943],"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":[0.0004961348,0.0001630823,0.001405345,0.0001550822,0.00007277275,0.0002985248,0.0002606776,0.6607125,0.07632867,0.05841932,0.002450627,0.1992372],"study_design_scores_gemma":[0.00001846441,0.00007984583,0.0001386647,0.000005147833,0.000008681316,0.00006025821,0.00001176171,0.9817077,0.0118305,0.004930689,0.001198397,0.000009848051],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04180983,0.0001385428,0.9532633,0.0001552061,0.00006506197,0.00005377781,0.00003395808,0.001830784,0.002649566],"genre_scores_gemma":[0.969139,0.00007524002,0.02945909,0.00004751415,0.00002066854,0.00004086837,0.00003955844,0.00003019238,0.001147803],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001454516,"threshold_uncertainty_score":0.004865766,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07785579363795478,"score_gpt":0.3010935727640066,"score_spread":0.2232377791260518,"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."}}