{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001898402,0.0006519597,0.0005276678,0.001261697,0.0003582682,0.0007192619,0.0005014684,0.0004984615,0.0004919291],"category_scores_gemma":[0.005742109,0.0001341221,0.0006983974,0.000713677,0.0006958533,0.001487068,0.0004479198,0.0007137281,0.0001966809],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006018043,"about_ca_system_score_gemma":0.0005971959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001263738,"about_ca_topic_score_gemma":0.001402045,"domain_scores_codex":[0.9985258,0.0004440506,0.0001615617,0.0002714678,0.0004461907,0.0001510235],"domain_scores_gemma":[0.9935223,0.003359533,0.00115795,0.0008635818,0.001004799,0.00009179792],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001384891,0.001930125,0.1444692,0.0005749632,0.0007547011,0.0005804392,0.0004775955,0.5001076,0.04146457,0.003370105,0.00291244,0.3019733],"study_design_scores_gemma":[0.00001054379,0.0002923264,0.02303385,0.00002062763,0.00005094269,0.0002502404,0.0001442813,0.945381,0.02744224,0.002746574,0.0006027524,0.00002465491],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9204518,0.0003660286,0.07666066,0.0002783956,0.00004005073,0.00005516584,0.0003956052,0.0006021103,0.001150249],"genre_scores_gemma":[0.9852824,0.00006825515,0.01366886,0.00002900174,0.00001095794,0.00002179045,0.0006000708,0.00001742945,0.0003012156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001898402,"threshold_uncertainty_score":0.01003987,"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."}}