{"id":"W2948743103","doi":"10.1109/lcsys.2019.2920507","title":"Resilient Control for Cyber-Physical Systems Subject to Replay Attacks","year":2019,"lang":"en","type":"article","venue":"IEEE Control Systems Letters","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":94,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Replay attack; Model predictive control; Controller (irrigation); Cyber-physical system; State (computer science); Control (management); Horizon; Set (abstract data type); Subject (documents); Action (physics); Bounded function; Control theory (sociology); Computer security; Artificial intelligence; Algorithm; Mathematics","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008190075,0.0008388918,0.0006393751,0.0003578944,0.0003717854,0.0009563317,0.0007992766,0.000759105,0.001148639],"category_scores_gemma":[0.002087638,0.0002087666,0.0005021335,0.000275005,0.001225698,0.00106185,0.001102152,0.001216322,0.0001963327],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005614528,"about_ca_system_score_gemma":0.0005398572,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001201775,"about_ca_topic_score_gemma":0.000700416,"domain_scores_codex":[0.9992958,0.0001791321,0.00003989274,0.0001619358,0.0002389398,0.00008424757],"domain_scores_gemma":[0.9993352,0.0002740878,0.0001526131,0.000115566,0.0001007563,0.00002173068],"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":[0.0001582357,0.00003834798,0.0002302806,0.0001756337,0.00005954327,0.0002651457,0.0002082544,0.8381156,0.01627158,0.1053484,0.0009937361,0.0381352],"study_design_scores_gemma":[0.000009349374,0.0001136163,0.00005919618,0.00001036514,0.000007417953,0.00002732823,0.00001287917,0.9848965,0.002222292,0.01183979,0.0007932381,0.000007988948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01766477,0.0002369935,0.978284,0.0002906235,0.00009834586,0.00003337419,0.00001517057,0.0002128568,0.00316387],"genre_scores_gemma":[0.9749654,0.0003127252,0.02253789,0.0001324154,0.00006704878,0.00005260104,0.00002142566,0.00002333485,0.001887201],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001201775,"threshold_uncertainty_score":0.00433141,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005788247772184108,"score_gpt":0.2118930823617485,"score_spread":0.2061048345895644,"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."}}