{"id":"W3080123385","doi":"10.1145/3407023.3409216","title":"Exploring data leakage in encrypted payload using supervised machine learning","year":2020,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Payload (computing); Computer science; Encryption; Leakage (economics); Artificial intelligence; Embedded system; Machine learning; Operating system; Computer network","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":[0.0002883129,0.00010852,0.0001402383,0.0000834595,0.0001269185,0.0001282961,0.0009488611,0.00003491675,0.0001195108],"category_scores_gemma":[0.000100306,0.0001039726,0.00002346762,0.0008236461,0.00001298577,0.002547671,0.00104568,0.0003450513,0.00004965531],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002312558,"about_ca_system_score_gemma":0.00002249074,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004192302,"about_ca_topic_score_gemma":0.0000794854,"domain_scores_codex":[0.9987561,0.0001194979,0.0002250001,0.0004697035,0.0001954354,0.0002342239],"domain_scores_gemma":[0.9993439,0.00005268314,0.00004018065,0.0004451302,0.00001969758,0.00009835757],"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":[0.0001566282,0.0002518556,0.0145517,0.000159444,0.00006049851,0.0003581371,0.01965568,0.0618222,0.1708114,0.0190539,0.0004880283,0.7126306],"study_design_scores_gemma":[0.0002761434,0.00004905758,0.0003750881,0.00001686473,0.000001773946,0.000004735162,0.00007414538,0.9920076,0.002450029,0.00005318264,0.004555206,0.0001361519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4955667,0.0001530088,0.5012891,0.001314018,0.0002707707,0.0001145826,0.000001360077,0.0003833676,0.000907033],"genre_scores_gemma":[0.9763101,0.0001638527,0.02279043,0.0005725489,0.0001306729,0.000002741383,0.00001016443,0.000008647994,0.00001086362],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9301854,"threshold_uncertainty_score":0.423988,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2794331490435649,"score_gpt":0.2765292883410547,"score_spread":0.002903860702510197,"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."}}