{"id":"W4399973156","doi":"10.36287/setsci.17.1.0013","title":"Intrusion detection system using Optimized Machine Learning Algorithms for cyberattacks in the Internet of Vehicles (IoV)","year":2019,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Intrusion detection system; The Internet; Algorithm; Internet of Things; Computer network; Computer security; Machine learning; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001109887,0.0009140287,0.001120559,0.001456203,0.0004671846,0.0008108698,0.0007615536,0.0007332884,0.0005621928],"category_scores_gemma":[0.00212178,0.0003071691,0.0007896959,0.0007583708,0.0002438117,0.0006421654,0.0003924086,0.0007721746,0.0002385913],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009992922,"about_ca_system_score_gemma":0.0009371761,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008464496,"about_ca_topic_score_gemma":0.00527537,"domain_scores_codex":[0.9995103,0.0001018751,0.00004428697,0.0001363934,0.0001245712,0.00008256743],"domain_scores_gemma":[0.999319,0.0002965615,0.00009032674,0.00003147334,0.0002396615,0.00002308069],"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":[0.0002084634,0.0004100144,0.007301063,0.0001008597,0.0001528068,0.0001252162,0.00006538157,0.7282521,0.005687478,0.001034959,0.002336214,0.2543254],"study_design_scores_gemma":[0.000005524763,0.00004492537,0.0006609288,0.000003327488,0.000009613441,0.00001597692,0.000007741216,0.9974558,0.0013848,0.0002176394,0.0001896014,0.000004096531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3337346,0.001301085,0.6555682,0.0004665465,0.0001856089,0.0002765,0.0002841538,0.004908256,0.003275125],"genre_scores_gemma":[0.850541,0.0002818847,0.146622,0.0001077792,0.00003036621,0.0001813793,0.0005981227,0.00005690614,0.001580561],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008464496,"threshold_uncertainty_score":0.01683044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01910083993994591,"score_gpt":0.249313725374609,"score_spread":0.2302128854346631,"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."}}