{"id":"W4382360845","doi":"10.1051/sands/2023017","title":"Event-triggered resilient consensus control of multiple unmanned systems against periodic DoS attacks based on state predictor","year":2023,"lang":"en","type":"article","venue":"Security and Safety","topic":"Distributed Control Multi-Agent Systems","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Education, Science and Technology; Fundamental Research Funds for the Central Universities; Natural Science Foundation of Jiangsu Province; Government of Jiangsu Province; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Control theory (sociology); Computer science; Denial-of-service attack; Controller (irrigation); Resilience (materials science); State (computer science); Consensus; Multi-agent system; Control (management); Artificial intelligence; Algorithm","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":[0.0005088394,0.0004535706,0.0004150063,0.0002000463,0.0003667633,0.0004653638,0.0006950026,0.0003591533,0.0005336546],"category_scores_gemma":[0.001020581,0.0001852676,0.0003321901,0.0001857519,0.0004680099,0.000526469,0.0006892114,0.0007176057,0.0000856008],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002980625,"about_ca_system_score_gemma":0.0007731985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002825163,"about_ca_topic_score_gemma":0.001726896,"domain_scores_codex":[0.9996372,0.00005731079,0.00001951244,0.0001281726,0.0001173398,0.00004027709],"domain_scores_gemma":[0.9995778,0.0001202679,0.000120861,0.00004807932,0.0001082819,0.00002464905],"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":[0.0001141557,0.00004834806,0.0008192305,0.00006701648,0.00004254946,0.0001395622,0.0001882746,0.9165521,0.02042274,0.009091123,0.0003726173,0.05214225],"study_design_scores_gemma":[0.000007545964,0.0000663728,0.0001436903,0.000002426106,0.000005648659,0.00001047209,0.000006712224,0.9966894,0.001973504,0.0008458449,0.000244064,0.00000427732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0468407,0.0001035488,0.9510541,0.00009355987,0.00004678366,0.00003110415,0.00001186881,0.0003705135,0.001447778],"genre_scores_gemma":[0.9771535,0.00008003721,0.02162367,0.00003360381,0.00001439126,0.00003957575,0.00002223764,0.000009281358,0.0010237],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.002825163,"threshold_uncertainty_score":0.00561738,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01050089176661124,"score_gpt":0.2305241262517268,"score_spread":0.2200232344851155,"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."}}