{"id":"W2907471780","doi":"10.1109/jiot.2018.2890728","title":"Toward Secure and Scalable Computation in Internet of Things Data Applications","year":2019,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"National Natural Science Foundation of China; Louisiana Board of Regents","keywords":"Computer science; Server; Homomorphic encryption; Scalability; Distributed computing; Encryption; Overhead (engineering); Cloud computing; Computer network; Correctness; The Internet; Database; Operating system; Algorithm","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":[0.0008824698,0.000123693,0.0002650484,0.0002794121,0.00001911,0.0001759868,0.001789963,0.00007819838,0.00002682242],"category_scores_gemma":[0.00002858071,0.0001137786,0.00005732905,0.0002948002,0.0000786965,0.002497026,0.000619581,0.0004322936,0.000008461053],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002268026,"about_ca_system_score_gemma":0.00004553523,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003825435,"about_ca_topic_score_gemma":0.000007643152,"domain_scores_codex":[0.9985785,0.0000640259,0.0005409516,0.0003287286,0.0003136047,0.0001741163],"domain_scores_gemma":[0.9987461,0.0001137345,0.0004644278,0.0004627519,0.0001329853,0.00007998423],"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":[0.0006041725,0.002491231,0.1272863,0.002445249,0.0008485813,0.0001083989,0.1809486,0.0008101313,0.02870065,0.2793677,0.05464602,0.3217429],"study_design_scores_gemma":[0.002242974,0.0005336642,0.005141847,0.001240048,0.00004374324,0.0007483456,0.0005905713,0.895026,0.01245196,0.0740763,0.007354172,0.0005503276],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2359523,0.0002900051,0.7624764,0.0002499078,0.0003234867,0.000153215,0.000008703381,0.00001946195,0.000526502],"genre_scores_gemma":[0.925711,0.00005919018,0.07398628,0.0001741327,0.00002795596,0.000001786766,0.00001467494,0.000006329686,0.00001868818],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8942159,"threshold_uncertainty_score":0.4639756,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02617800220480961,"score_gpt":0.2719697092970974,"score_spread":0.2457917070922877,"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."}}