{"id":"W4387951196","doi":"10.1109/ccece58730.2023.10289070","title":"Dark Web Traffic Detection Using Supervised Machine Learning","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Victoria","funders":"","keywords":"Computer science; Deep Web; Naive Bayes classifier; Random forest; Machine learning; Decision tree; Traffic classification; The Internet; Cross-validation; C4.5 algorithm; Support vector machine; Artificial intelligence; Router; Anonymity; Network packet; Data mining; Computer security; Computer network; 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":[0.001635814,0.001050253,0.001036017,0.003380482,0.0005162654,0.001075132,0.001113914,0.0008231877,0.0005699098],"category_scores_gemma":[0.005715823,0.000262822,0.0006777034,0.001373032,0.0004527766,0.001360946,0.0004790846,0.0008231782,0.0006211101],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007097901,"about_ca_system_score_gemma":0.0009373236,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003575125,"about_ca_topic_score_gemma":0.003648865,"domain_scores_codex":[0.9985899,0.0004651777,0.0001168031,0.000301362,0.0003879729,0.0001388064],"domain_scores_gemma":[0.9942934,0.002828824,0.0008030027,0.0005544754,0.001386586,0.0001336674],"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":[0.0004140099,0.001683204,0.04334795,0.0003040095,0.0002206523,0.0002787366,0.0001794553,0.3730092,0.009135595,0.003145305,0.008064018,0.5602179],"study_design_scores_gemma":[0.000004287144,0.00003658192,0.001606647,0.00001045923,0.000006287305,0.00003518841,0.00002317913,0.9945489,0.002232033,0.001108925,0.0003808303,0.00000666512],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4484628,0.0008210125,0.5392608,0.0004442855,0.0001492138,0.0003410603,0.001448024,0.005036239,0.004036587],"genre_scores_gemma":[0.8709092,0.0002153176,0.1242935,0.0000995133,0.0001036889,0.0001602373,0.00278219,0.00007312419,0.001363263],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003575125,"threshold_uncertainty_score":0.008651137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02421034041698225,"score_gpt":0.2673377868322488,"score_spread":0.2431274464152666,"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."}}