{"id":"W4289713073","doi":"10.1109/netsoft54395.2022.9844082","title":"Encrypted Network Traffic Classification in SDN using Self-supervised Learning","year":2022,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Regina","funders":"","keywords":"Traffic classification; Computer science; Testbed; Encryption; Software-defined networking; Traffic generation model; Artificial intelligence; Machine learning; Field (mathematics); Supervised learning; Data mining; Computer network; Artificial neural network; Quality of service","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":[0.001228757,0.0004279177,0.0005011456,0.0005336934,0.0003599885,0.0005216085,0.0007014718,0.0005806836,0.0004011752],"category_scores_gemma":[0.002284833,0.0002151376,0.0003585113,0.0003289914,0.0004779327,0.0009045644,0.0004903565,0.0007840688,0.000136136],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007387534,"about_ca_system_score_gemma":0.0006822333,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004003306,"about_ca_topic_score_gemma":0.003616491,"domain_scores_codex":[0.9996018,0.0001162707,0.0000306279,0.0001000767,0.00009044076,0.00006078034],"domain_scores_gemma":[0.998621,0.0005629646,0.0001687206,0.0001665371,0.0004076998,0.00007307313],"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":[0.0003305038,0.0006495087,0.0120859,0.00004304299,0.00007362099,0.00009946206,0.0001017777,0.8188084,0.004632079,0.002103082,0.001493019,0.1595795],"study_design_scores_gemma":[0.0000014971,0.000007778941,0.0001783689,6.099169e-7,9.589852e-7,0.000003022078,0.000003229296,0.9989851,0.0005198669,0.0002721254,0.00002632219,0.000001034407],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4965354,0.0001633535,0.4995348,0.0003330927,0.00007383608,0.00009114845,0.000109232,0.001415012,0.001744248],"genre_scores_gemma":[0.9640899,0.00003546614,0.03485291,0.00004710092,0.00002306903,0.00002839448,0.0001446404,0.00002594721,0.0007525928],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004003306,"threshold_uncertainty_score":0.007960021,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02402596565499038,"score_gpt":0.2403301742440528,"score_spread":0.2163042085890624,"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."}}