{"id":"W7101589494","doi":"10.1109/tdsc.2025.3626379","title":"SXGB: Secure and Efficient Vertical Federated XGBoost via Trusted Execution Environments","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Education and Cultural Studies","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"National Natural Science Foundation of China","keywords":"Homomorphic encryption; Scheme (mathematics); Encryption; Speedup; Inference; Cloud computing; ENCODE; Information privacy; Data sharing; Cryptography","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":[0.001935826,0.0006649024,0.000890111,0.0004665722,0.0009737618,0.001254404,0.001913021,0.001012113,0.001851755],"category_scores_gemma":[0.003400306,0.0003056186,0.0005719539,0.0006867308,0.001361063,0.001931557,0.002985224,0.001451028,0.0008078442],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001066001,"about_ca_system_score_gemma":0.00251803,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00321848,"about_ca_topic_score_gemma":0.002753326,"domain_scores_codex":[0.9979103,0.0005791643,0.00009109214,0.0003260412,0.0005942509,0.000499095],"domain_scores_gemma":[0.9987514,0.0002479464,0.0001831848,0.0005015979,0.0001943542,0.0001214856],"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":[0.00344317,0.0004308579,0.004573534,0.0002555722,0.0002285498,0.0004201959,0.0005613678,0.54891,0.03156584,0.05712662,0.01025824,0.342226],"study_design_scores_gemma":[0.00008615317,0.0001015989,0.0002582687,0.00001242739,0.00001332354,0.00006796545,0.00004158157,0.9779805,0.006448318,0.01314449,0.001829927,0.00001542698],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0693922,0.0003864927,0.9227563,0.0003126354,0.00008487632,0.0001494428,0.00009129516,0.004799278,0.002027348],"genre_scores_gemma":[0.8591774,0.0001257655,0.1372414,0.0001740985,0.00002813296,0.0001598305,0.0002141227,0.0001934868,0.002685709],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.00321848,"threshold_uncertainty_score":0.01023775,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01240025183698758,"score_gpt":0.2713866850307167,"score_spread":0.2589864331937292,"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."}}