{"id":"W4206078274","doi":"10.30534/ijeter/2021/23942021","title":"Proposed Back Propagation Deep Neural Network for Intrusion Detection in Internet of Things Fog Computing","year":2021,"lang":"en","type":"article","venue":"International Journal of Emerging Trends in Engineering Research","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Cloud computing; Denial-of-service attack; Computer security; Botnet; Intrusion detection system; The Internet; Fog computing; IPv6; Computer network; Internet of Things; World Wide Web; 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":[0.0005401642,0.000767371,0.0006735701,0.0004833681,0.0003326483,0.0006893332,0.001219512,0.001025422,0.0008927631],"category_scores_gemma":[0.0007352277,0.0003443568,0.0006820562,0.0005015552,0.0002847331,0.0008189416,0.0004702846,0.001369771,0.0003010144],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009088672,"about_ca_system_score_gemma":0.0009313081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01666383,"about_ca_topic_score_gemma":0.01370183,"domain_scores_codex":[0.9997541,0.00002789449,0.00001742977,0.00007172884,0.00006714732,0.0000617621],"domain_scores_gemma":[0.9997827,0.00005162071,0.00001825225,0.00001439532,0.0001184018,0.00001462986],"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":[0.0002957766,0.0004171857,0.005336573,0.0001514851,0.0002439901,0.0002737555,0.00008725614,0.6146303,0.01198443,0.003245439,0.006632789,0.356701],"study_design_scores_gemma":[0.000003562999,0.00002469966,0.0002585957,0.000004841687,0.00001111952,0.00001306697,0.000003782303,0.9979657,0.001106605,0.0003584668,0.0002457545,0.000003900235],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1322495,0.002665754,0.8514249,0.001373776,0.0005817311,0.0001592254,0.0005181569,0.003909983,0.007117051],"genre_scores_gemma":[0.8847941,0.001003602,0.1037962,0.0005284437,0.00007834303,0.0001339403,0.0008630984,0.00006164017,0.008740656],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01666383,"threshold_uncertainty_score":0.03313363,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03014034179993306,"score_gpt":0.3257358528818738,"score_spread":0.2955955110819407,"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."}}