{"id":"W3081866196","doi":"10.2478/popets-2020-0049","title":"Mitigator: Privacy policy compliance using trusted hardware","year":2020,"lang":"en","type":"article","venue":"Proceedings on Privacy Enhancing Technologies","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Trusted computing base; Computer security; Compliance (psychology); Privacy policy; Overhead (engineering); Privacy by Design; Software; Information privacy; Access control; Operating system; Cloud computing; Cloud computing security","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":[0.006047995,0.0009257063,0.0008503323,0.001171979,0.001282396,0.00301206,0.003061323,0.001832011,0.005509418],"category_scores_gemma":[0.01939989,0.0009397061,0.0008924914,0.000626745,0.002833619,0.004638954,0.004745882,0.004127893,0.002043779],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001127505,"about_ca_system_score_gemma":0.002536889,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001093881,"about_ca_topic_score_gemma":0.0006632029,"domain_scores_codex":[0.9872366,0.003728388,0.0008725178,0.001410951,0.005414028,0.001337468],"domain_scores_gemma":[0.9755352,0.005625392,0.003278869,0.01224197,0.002798414,0.0005200937],"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":[0.003978554,0.001344968,0.02475059,0.001939459,0.0006800183,0.003110131,0.002810245,0.06504221,0.2774456,0.1991546,0.03482772,0.3849161],"study_design_scores_gemma":[0.0003999028,0.001100414,0.002535665,0.0003583574,0.0003357455,0.001422313,0.0003414408,0.4117709,0.4949504,0.03598929,0.05054175,0.0002538677],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1316158,0.0005020878,0.8014325,0.001217763,0.0002892928,0.000773321,0.0001889068,0.05356412,0.01041615],"genre_scores_gemma":[0.8084759,0.0002199772,0.1841291,0.0005228529,0.0000874571,0.0002300843,0.0002165922,0.001359259,0.00475878],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006047995,"threshold_uncertainty_score":0.03198522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08761931710838279,"score_gpt":0.3088340749691185,"score_spread":0.2212147578607357,"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."}}