{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008896236,0.0001264507,0.0001863609,0.00016808,0.0003716891,0.0001304949,0.0006508523,0.00003918789,0.0002352014],"category_scores_gemma":[0.00001647261,0.0001285195,0.00009498701,0.00120423,0.00001068077,0.0002269758,0.000253393,0.0004191755,0.00001581295],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001821885,"about_ca_system_score_gemma":0.00007201455,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002226302,"about_ca_topic_score_gemma":0.00004568556,"domain_scores_codex":[0.9981456,0.0003519428,0.0003691845,0.000426739,0.0003453005,0.0003612082],"domain_scores_gemma":[0.9995413,0.00008074428,0.0001112972,0.0001762626,0.00004045773,0.00004987822],"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":[0.000002742934,0.00006033633,0.0005528327,0.000002759356,0.00001601537,0.00001039719,0.002121673,0.9222472,0.0000805474,0.06725948,0.0001296757,0.007516375],"study_design_scores_gemma":[0.0002065962,0.0000419536,0.000493283,0.000006176949,0.000007810038,0.00001044988,0.0006940502,0.9970024,0.000003604737,0.000009243603,0.001364785,0.0001597084],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6117562,0.0000690141,0.3860434,0.0001725734,0.0002262947,0.0001063323,1.143981e-7,0.0003277784,0.001298241],"genre_scores_gemma":[0.969215,0.000003172663,0.03031521,0.0001857759,0.00007891985,0.00001252852,0.000006220538,0.00001038155,0.000172825],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3574587,"threshold_uncertainty_score":0.5240875,"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."}}