{"id":"W3167091510","doi":"10.1109/syscon48628.2021.9447072","title":"Efficient Traffic Classification Using Hybrid Deep Learning","year":2021,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Traffic classification; Computer science; Artificial intelligence; Machine learning; Convolutional neural network; Deep learning; Binary classification; Multiclass classification; Artificial neural network; Recurrent neural network; Data mining; Quality of service; Support vector machine; Computer network","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000294039,0.0001128705,0.0001501508,0.0000796725,0.0001889524,0.0002499475,0.0003259674,0.00003392819,0.0001111769],"category_scores_gemma":[0.00005754385,0.0001038955,0.0001277701,0.0004006686,0.00001926184,0.00008264424,0.0001166896,0.0001784658,0.0000843329],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006325779,"about_ca_system_score_gemma":0.0000577602,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002544592,"about_ca_topic_score_gemma":0.00001196151,"domain_scores_codex":[0.9986525,0.0001136835,0.0002667586,0.0004344438,0.0002740609,0.0002585759],"domain_scores_gemma":[0.999421,0.00005827402,0.00008985685,0.0001970654,0.0001654665,0.0000683596],"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":[6.515358e-7,0.00005513931,0.00002169764,0.000004288387,0.00002038381,0.00003342417,0.0004772063,0.8571455,0.0009316724,0.1118758,0.00003497107,0.02939927],"study_design_scores_gemma":[0.00009183845,0.00001093227,0.0001067979,0.00001137547,0.00001193295,0.00005402399,0.0002409877,0.9981447,0.0006469547,0.000003382529,0.0005418131,0.0001352152],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3560634,0.00009716643,0.6418812,0.0001154098,0.0001471169,0.00002259747,7.169538e-8,0.0001334832,0.001539488],"genre_scores_gemma":[0.9752062,0.000003081749,0.02407511,0.000118873,0.00006649314,0.000001333196,0.000004788581,0.00000775943,0.0005163412],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6191428,"threshold_uncertainty_score":0.4236737,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357637689426253,"score_gpt":0.2507384555261722,"score_spread":0.2271620786319097,"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."}}