{"id":"W4396535419","doi":"10.1109/tifs.2024.3394678","title":"Revocable and Privacy-Preserving Bilateral Access Control for Cloud Data Sharing","year":2024,"lang":"en","type":"article","venue":"IEEE Transactions on Information Forensics and Security","topic":"Cryptography and Data Security","field":"Computer Science","cited_by":21,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Cloud computing; Computer security; Access control; Information privacy; Internet privacy; Data sharing; Operating system","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[{"model":"gemma","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"empirical","about_ca_system":false,"about_ca_topic":false,"confidence":"low","status":"direct model label, unvalidated"},{"model":"gpt","categories":[],"domain":null,"study_design":"theoretical_or_conceptual","genre":"methods","about_ca_system":false,"about_ca_topic":false,"confidence":"high","status":"direct model label, unvalidated"}],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003199022,0.0005602783,0.001055488,0.0005272314,0.001141934,0.001815894,0.002401652,0.001138492,0.001939809],"category_scores_gemma":[0.00590427,0.0003135109,0.001021661,0.0007684174,0.001506711,0.004972077,0.003316577,0.001763028,0.0004785955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001106828,"about_ca_system_score_gemma":0.001540932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001456636,"about_ca_topic_score_gemma":0.0008510525,"domain_scores_codex":[0.993775,0.001747748,0.0004442163,0.001314475,0.001988768,0.0007297944],"domain_scores_gemma":[0.9960828,0.0009259774,0.0006656195,0.001490569,0.0006155164,0.0002194476],"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":[0.001481791,0.000331381,0.002476911,0.0004788103,0.0002582883,0.0007495813,0.001454813,0.16086,0.06925638,0.5010208,0.003886396,0.2577449],"study_design_scores_gemma":[0.0001588501,0.0002846097,0.0004471441,0.00003508365,0.00007298961,0.0007314651,0.0001961371,0.8381881,0.02108369,0.1261966,0.0124787,0.0001266234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02618914,0.0003206198,0.9699466,0.0002342598,0.00005699693,0.0001289067,0.00006754226,0.0004114588,0.002644586],"genre_scores_gemma":[0.9217819,0.0002342816,0.07470892,0.0001778837,0.0000636656,0.0001470622,0.00009851894,0.00004026144,0.002747569],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003199022,"threshold_uncertainty_score":0.01691824,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03604402686750368,"score_gpt":0.2895639709391531,"score_spread":0.2535199440716495,"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."}}