{"id":"W7115918670","doi":"10.32604/cmc.2025.074897","title":"A Comparative Benchmark of Machine and Deep Learning for Cyberattack Detection in IoT Networks","year":2025,"lang":"en","type":"article","venue":"Computers, materials & continua/Computers, materials & continua (Print)","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Chicoutimi","funders":"","keywords":"Benchmark (surveying); Deep learning; Metric (unit); Intrusion detection system; Internet of Things; Botnet; Selection (genetic algorithm); Precision and recall","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":[0.003982013,0.001688745,0.0006747745,0.002634434,0.0005932723,0.0009863056,0.001342024,0.001257616,0.0008354297],"category_scores_gemma":[0.007719308,0.0002563454,0.0004838901,0.001739604,0.0006701141,0.002099587,0.001256088,0.001024844,0.0004777266],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001543235,"about_ca_system_score_gemma":0.0009102936,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01154627,"about_ca_topic_score_gemma":0.0147468,"domain_scores_codex":[0.9977718,0.0007148786,0.000157399,0.0004519447,0.0006751164,0.0002288274],"domain_scores_gemma":[0.9967284,0.001444739,0.0002415613,0.0005276417,0.0008868577,0.0001707868],"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":[0.001121443,0.001125811,0.0285431,0.000603211,0.0003632776,0.0002512555,0.0001221952,0.6514143,0.006391462,0.005087973,0.02105357,0.2839225],"study_design_scores_gemma":[0.00004331402,0.0004188251,0.005942453,0.00006167599,0.00002796696,0.00008590378,0.0001048376,0.9803712,0.0071071,0.002657065,0.003158435,0.00002117887],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8489116,0.006827005,0.1060657,0.002073104,0.0007353284,0.000440455,0.004648718,0.006340633,0.02395743],"genre_scores_gemma":[0.9236506,0.001181638,0.06354284,0.000398557,0.0001188825,0.0001748872,0.008291908,0.0002115356,0.002429157],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01154627,"threshold_uncertainty_score":0.0229581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008791581505577718,"score_gpt":0.2428821813819964,"score_spread":0.2340905998764187,"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."}}