{"id":"W3015426006","doi":"10.1109/isncc49221.2020.9297290","title":"Multi-stage Jamming Attacks Detection using Deep Learning Combined with Kernelized Support Vector Machine in 5G Cloud Radio Access Networks","year":2020,"lang":"en","type":"preprint","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Computer science; Intrusion detection system; Jamming; Cloud computing; Support vector machine; Software deployment; Wireless; Deep learning; Artificial intelligence; Computer network; Machine learning; Telecommunications","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":[0.0007803415,0.0008222642,0.0006752409,0.0005558727,0.0002373511,0.0005245806,0.0007611553,0.0005608342,0.0004419545],"category_scores_gemma":[0.001415009,0.0002708838,0.0004447162,0.0003994914,0.0002995812,0.0007058501,0.000591884,0.0009875101,0.000172214],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006144072,"about_ca_system_score_gemma":0.0005409268,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006823515,"about_ca_topic_score_gemma":0.005069263,"domain_scores_codex":[0.9995851,0.0001085358,0.00002465577,0.00007341168,0.00009004044,0.0001182506],"domain_scores_gemma":[0.9994187,0.0002385871,0.00006874953,0.0000522925,0.0001740539,0.00004762512],"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":[0.0009149094,0.0006149187,0.01008269,0.0000999007,0.0001757226,0.0002760997,0.0001131046,0.6147338,0.01461261,0.00174665,0.002440924,0.3541887],"study_design_scores_gemma":[0.000003317548,0.0000318308,0.0004870661,0.000001747158,0.000005040988,0.000008624536,0.000007110464,0.9974112,0.001710694,0.0002546743,0.00007552786,0.000003283244],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.538219,0.001051731,0.454789,0.0006048707,0.00009805515,0.0000759258,0.000173154,0.002758805,0.002229468],"genre_scores_gemma":[0.9600635,0.0001327445,0.03836139,0.00007051061,0.00002013395,0.00002373438,0.0001869854,0.00002288996,0.001118075],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.006823515,"threshold_uncertainty_score":0.01356757,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04709690538799374,"score_gpt":0.2981512491828885,"score_spread":0.2510543437948948,"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."}}