{"id":"W4385522546","doi":"10.56553/popets-2023-0107","title":"Trifecta: Faster High-Throughput Three-Party Computation over WAN Using Multi-Fan-In Logic Gates","year":2023,"lang":"en","type":"article","venue":"Proceedings on Privacy Enhancing Technologies","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada; Royal Bank of Canada; Amazon Web Services","keywords":"Precomputation; Computer science; Computation; Throughput; Latency (audio); Computer network; Constant (computer programming); Reduction (mathematics); Wide area network; Distributed computing; Algorithm; Telecommunications; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00127416,0.0006095073,0.0006056236,0.0005884315,0.0008329092,0.00122413,0.001446532,0.000555111,0.00524671],"category_scores_gemma":[0.001163142,0.0002468737,0.0006900781,0.0005460753,0.0009647475,0.002930535,0.001669003,0.001301176,0.0009170352],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006613246,"about_ca_system_score_gemma":0.0008703828,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005763224,"about_ca_topic_score_gemma":0.0007118342,"domain_scores_codex":[0.9990938,0.0002467831,0.00005574827,0.0001409175,0.000271361,0.0001915449],"domain_scores_gemma":[0.9989574,0.0003096135,0.0001224821,0.0004483181,0.0001010661,0.00006105431],"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":[0.002863193,0.0007740961,0.002249782,0.0007937278,0.0002808169,0.001096311,0.0006305375,0.0960017,0.2389892,0.297731,0.02340274,0.3351869],"study_design_scores_gemma":[0.0003218653,0.0008626592,0.0005278931,0.00006068244,0.0001045001,0.0006912201,0.0001186514,0.7800405,0.1343306,0.05375746,0.02909484,0.00008903601],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1060793,0.0005561738,0.8690301,0.0004363358,0.0001667841,0.0003459643,0.0002171229,0.006954139,0.01621419],"genre_scores_gemma":[0.8304129,0.000246766,0.1626124,0.0002213741,0.00003992328,0.0002645073,0.0003718643,0.0002618359,0.005568421],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00524671,"threshold_uncertainty_score":0.01755196,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04713547527083255,"score_gpt":0.3015057539636992,"score_spread":0.2543702786928667,"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."}}