{"id":"W4390142817","doi":"10.1007/s12083-023-01597-4","title":"Unveiling DoH tunnel: Toward generating a balanced DoH encrypted traffic dataset and profiling malicious behavior using inherently interpretable machine learning","year":2023,"lang":"en","type":"article","venue":"Peer-to-Peer Networking and Applications","topic":"Internet Traffic Analysis and Secure E-voting","field":"Computer Science","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"York University","funders":"","keywords":"Overfitting; Interpretability; Computer science; Profiling (computer programming); Random forest; Data mining; Machine learning; Encryption; Artificial intelligence; The Internet; Artificial neural network; Computer security; 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":[0.00161576,0.000702048,0.0005545198,0.001824136,0.0005546922,0.0008248421,0.0008102827,0.00100599,0.0006378833],"category_scores_gemma":[0.006000503,0.0002556445,0.0004000972,0.0007830223,0.0005942978,0.001671707,0.001427345,0.001260872,0.0007811454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005129767,"about_ca_system_score_gemma":0.0009494093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001770789,"about_ca_topic_score_gemma":0.003929751,"domain_scores_codex":[0.99891,0.0002490609,0.00006250558,0.0002481384,0.0003674092,0.0001630067],"domain_scores_gemma":[0.996618,0.0007701339,0.0004203146,0.001260452,0.0007817094,0.0001493634],"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":[0.001359452,0.002719343,0.1734373,0.000497526,0.0003650821,0.0008419513,0.0007498382,0.2918088,0.06873479,0.02861944,0.05505446,0.375812],"study_design_scores_gemma":[0.00003177865,0.0001941593,0.0128586,0.00002604836,0.00002854021,0.0002430275,0.0001992337,0.9497024,0.016685,0.01230568,0.007696591,0.00002898428],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6236992,0.0003544103,0.3435104,0.001051999,0.0002542363,0.0004427193,0.01631682,0.00916087,0.005209375],"genre_scores_gemma":[0.886254,0.0001217913,0.08707,0.0002118421,0.00008984513,0.0001876466,0.02383733,0.0002709445,0.0019566],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001824136,"threshold_uncertainty_score":0.008545101,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03281763495495147,"score_gpt":0.293704309409292,"score_spread":0.2608866744543405,"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."}}