{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005271552,0.0001175387,0.0001444665,0.0001318137,0.0001678779,0.0001376096,0.0004528722,0.00007291384,0.00001861505],"category_scores_gemma":[0.00003370365,0.0001047423,0.000124864,0.0008299662,0.00001790795,0.0002395713,0.00004441019,0.00007896714,0.000186165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004710486,"about_ca_system_score_gemma":0.00004904738,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00000501426,"about_ca_topic_score_gemma":0.0001886064,"domain_scores_codex":[0.9987415,0.00004886982,0.0003021528,0.0003844698,0.0001918397,0.0003311473],"domain_scores_gemma":[0.9993612,0.0001656848,0.0001066173,0.0001935755,0.0001200504,0.00005286947],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000004187094,0.00001703141,0.000003889127,0.000008623274,0.00002819911,0.000001351558,0.0009892276,0.4401798,0.00006019252,0.4833499,0.006223137,0.06913447],"study_design_scores_gemma":[0.0001508052,0.0000403686,0.0005718082,0.000007572017,0.00001209332,0.000001270258,0.0003639003,0.9969347,0.000005941599,0.0002567161,0.001521635,0.0001331948],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02884905,0.00003207218,0.9684866,0.0007302734,0.0004162847,0.000203735,8.215485e-7,0.0006822305,0.0005989149],"genre_scores_gemma":[0.9813696,0.0000112136,0.01670966,0.0001436385,0.0001056639,0.00004992284,0.00008214782,0.00001138676,0.001516784],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9525205,"threshold_uncertainty_score":0.4271267,"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."}}