{"id":"W4395017388","doi":"10.1109/tdsc.2024.3392424","title":"MaskCrypt: Federated Learning With Selective Homomorphic Encryption","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Homomorphic encryption; Computer science; Encryption; Computer security; Theoretical computer science","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":[0.0002871162,0.000248069,0.0002039537,0.0003055122,0.0009078769,0.0008538538,0.00021226,0.0001117161,0.00001980574],"category_scores_gemma":[0.000003084211,0.000215388,0.00007763829,0.001150685,0.00005640665,0.0007386187,0.000007089018,0.0008174072,0.00003458577],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004065922,"about_ca_system_score_gemma":0.00009092534,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006963041,"about_ca_topic_score_gemma":0.0001169906,"domain_scores_codex":[0.9983554,0.0001177199,0.000211971,0.0006747533,0.0002700197,0.0003701193],"domain_scores_gemma":[0.9993196,0.0002238099,0.0000470767,0.0001966767,0.00008797443,0.0001248294],"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":[0.0003120833,0.0007001911,0.0004086751,0.0006808004,0.0009375083,0.001147829,0.01564925,0.1698789,0.005927251,0.07723765,0.0008083254,0.7263116],"study_design_scores_gemma":[0.0005207041,0.0005951236,0.0001220005,0.0003409779,0.00005330014,0.0003822319,0.0002996916,0.9834752,0.009603406,0.001751109,0.002356709,0.0004995341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07477573,0.0004249789,0.9227287,0.0001722868,0.0003743872,0.0001691452,0.000007733074,0.001005885,0.000341183],"genre_scores_gemma":[0.9901606,0.00008381836,0.009566507,0.0000740929,0.00005626102,0.000008634778,0.000004795007,0.00002610684,0.00001916298],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9153849,"threshold_uncertainty_score":0.8783267,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008515883368515574,"score_gpt":0.2196670418634302,"score_spread":0.2111511584949146,"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."}}