{"id":"W4386223270","doi":"10.3390/s23177464","title":"Ensemble Model Based on Hybrid Deep Learning for Intrusion Detection in Smart Grid Networks","year":2023,"lang":"en","type":"article","venue":"Sensors","topic":"Smart Grid Security and Resilience","field":"Engineering","cited_by":71,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"King Abdulaziz University","keywords":"Computer science; Smart grid; Intrusion detection system; Reliability (semiconductor); Grid; Anomaly detection; Denial-of-service attack; Deep learning; SCADA; Resilience (materials science); Real-time computing; Distributed computing; Artificial intelligence; Computer security; Engineering; The Internet; Operating system","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001954925,0.0001129628,0.0001150419,0.0001883483,0.0001026863,0.00001711267,0.00006072356,0.00007771196,0.000003644162],"category_scores_gemma":[0.00007555941,0.0001169295,0.00005276321,0.0002991391,0.00001393215,0.00004153713,0.00001258459,0.0002631969,0.00003319053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005673704,"about_ca_system_score_gemma":0.000005391649,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001131595,"about_ca_topic_score_gemma":0.0001280665,"domain_scores_codex":[0.9992501,0.00002680882,0.0001389105,0.0001742478,0.0001085179,0.0003014628],"domain_scores_gemma":[0.9996591,0.0001502325,0.00001582576,0.0001124373,0.00001591616,0.0000464945],"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":[0.00003475974,0.000006541495,0.0001236256,0.00002781777,0.000002339965,0.000007190392,0.0001111817,0.9790819,0.001347538,0.000005942419,0.0001297295,0.01912138],"study_design_scores_gemma":[0.0002811755,0.00005006337,0.0007070171,0.00003457687,0.000003371803,0.000001624438,0.0000439391,0.9870069,0.01101126,0.00008805084,0.0006343191,0.0001376728],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.919231,0.00002071903,0.07893192,0.00003354835,0.0007890358,0.0001938722,0.000001410819,0.0004122955,0.0003861795],"genre_scores_gemma":[0.9993927,0.00005583746,0.0001805768,0.00003384987,0.0001846372,0.00002894809,0.0000190258,0.00003121627,0.0000732026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08016169,"threshold_uncertainty_score":0.4768246,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008659955713557698,"score_gpt":0.2089822610251784,"score_spread":0.2003223053116207,"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."}}