{"id":"W4400903658","doi":"10.1109/tdsc.2024.3432650","title":"Privacy-Preserving Fine-Grained Data Sharing With Dynamic Service for the Cloud-Edge IoT","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":26,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Internet of Things; Enhanced Data Rates for GSM Evolution; Information privacy; Edge computing; Computer security; Data sharing; Service (business); Computer network; Telecommunications; Operating system; Business","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":[0.001503471,0.0003826364,0.0007681238,0.0004332906,0.001229863,0.001486649,0.001486014,0.0007060718,0.001025902],"category_scores_gemma":[0.002894623,0.0002074321,0.0007605699,0.00123032,0.001173163,0.00392075,0.003300246,0.001138824,0.000295741],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00125343,"about_ca_system_score_gemma":0.001672687,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001477586,"about_ca_topic_score_gemma":0.001095095,"domain_scores_codex":[0.9976621,0.0004621817,0.000200724,0.000386434,0.0008569807,0.0004315277],"domain_scores_gemma":[0.9977782,0.000433866,0.0002495915,0.001099524,0.0002780111,0.0001608922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001426014,0.0004002194,0.00323182,0.0003410038,0.0001398159,0.0009117502,0.001037445,0.252012,0.09670109,0.4385044,0.006674514,0.1986199],"study_design_scores_gemma":[0.00005250906,0.0001720957,0.0004888461,0.00001520211,0.00003119984,0.0005787353,0.0001473628,0.8959001,0.01747015,0.07732972,0.007748123,0.00006595307],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05466628,0.0004006187,0.9414691,0.0003860714,0.00007156173,0.0001134837,0.000106434,0.0004013283,0.002385169],"genre_scores_gemma":[0.9411832,0.0001800575,0.05728841,0.0001245503,0.00003442922,0.00005429055,0.00009933235,0.00002499289,0.001010661],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001503471,"threshold_uncertainty_score":0.009094298,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04734162852839136,"score_gpt":0.2973497996101303,"score_spread":0.250008171081739,"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."}}