{"id":"W4385192299","doi":"10.23919/ifipnetworking57963.2023.10186403","title":"FSTC: Dynamic Category Adaptation for Encrypted Network Traffic Classification","year":2023,"lang":"en","type":"article","venue":"","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Encryption; Traffic classification; Protocol (science); Adaptation (eye); Artificial intelligence; Transfer of learning; The Internet; Machine learning; Internet traffic; Computer network; Data mining; Network packet; World Wide Web","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":[0.002149802,0.001580667,0.001187266,0.003337703,0.0009032695,0.001126226,0.003573606,0.00204015,0.002780312],"category_scores_gemma":[0.005317822,0.000319056,0.001162821,0.002039978,0.0008484502,0.002447663,0.002171373,0.002754281,0.002095179],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001631763,"about_ca_system_score_gemma":0.0019677,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01415613,"about_ca_topic_score_gemma":0.01557731,"domain_scores_codex":[0.9985581,0.0002519306,0.00007365586,0.0004647704,0.0003713441,0.0002800888],"domain_scores_gemma":[0.9978272,0.0006162893,0.0001353111,0.000525368,0.0007086725,0.0001870455],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0006293841,0.001356014,0.02110209,0.0001929661,0.0002369794,0.000262199,0.0002356522,0.1099618,0.008816488,0.005266151,0.05809112,0.7938492],"study_design_scores_gemma":[0.00002098631,0.00006542322,0.001304893,0.00001424546,0.00001852665,0.00006799909,0.00005911972,0.9873706,0.003169579,0.004551897,0.003338505,0.00001819116],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2893311,0.001761951,0.6511191,0.001284507,0.0009812429,0.0009242735,0.005978746,0.03926313,0.009355909],"genre_scores_gemma":[0.7857502,0.0003258452,0.1882275,0.0007208925,0.0002214405,0.0005538545,0.01519043,0.0005213611,0.008488532],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01415613,"threshold_uncertainty_score":0.02814746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03265975898450794,"score_gpt":0.2648274964087448,"score_spread":0.2321677374242368,"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."}}