{"id":"W4387667119","doi":"10.1145/3622850","title":"Quantifying and Mitigating Cache Side Channel Leakage with Differential Set","year":2023,"lang":"en","type":"article","venue":"Proceedings of the ACM on Programming Languages","topic":"Security and Verification in Computing","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"National Science Foundation","keywords":"Cache; Computer science; Side channel attack; Cache invalidation; Abstraction; Smart Cache; Information leakage; Cache algorithms; CPU cache; Parallel computing; Embedded system; Computer network; Cryptography; Computer 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":[0.002966647,0.001660775,0.001100239,0.003272638,0.0009294642,0.002490532,0.00195545,0.001022795,0.001900034],"category_scores_gemma":[0.01031925,0.0009716057,0.002399178,0.00158538,0.003991787,0.005539513,0.004120873,0.002772156,0.0004808437],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002293923,"about_ca_system_score_gemma":0.002899775,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001943999,"about_ca_topic_score_gemma":0.003094729,"domain_scores_codex":[0.9936845,0.001626209,0.0004407801,0.0007767921,0.002854062,0.0006175883],"domain_scores_gemma":[0.9894608,0.004832441,0.001194118,0.003273717,0.001059707,0.000179208],"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":[0.0006105949,0.0002883183,0.01368446,0.001119131,0.0004526101,0.0005621265,0.001183314,0.4140231,0.08880519,0.2507174,0.005624476,0.2229293],"study_design_scores_gemma":[0.00004355803,0.0002205717,0.0008906611,0.0001404807,0.0002228975,0.0002604313,0.0001145258,0.7560275,0.08180954,0.1518158,0.00835733,0.00009665385],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.04567717,0.0004280051,0.9427974,0.0002860191,0.00007650135,0.00009441099,0.0001982692,0.007568176,0.002874064],"genre_scores_gemma":[0.6369773,0.0004421953,0.358129,0.0004001202,0.00007346056,0.0002378556,0.0003989773,0.001208662,0.002132552],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003272638,"threshold_uncertainty_score":0.0166437,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04797152063757609,"score_gpt":0.2967396356833562,"score_spread":0.2487681150457801,"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."}}