{"id":"W7116407680","doi":"10.1109/tdsc.2025.3646011","title":"Efficient and Secure Data Sharing With Mobile Crowdsensing in Internet of Vehicles","year":2025,"lang":"","type":"article","venue":"IEEE Transactions on Dependable and Secure Computing","topic":"Mobile Crowdsensing and Crowdsourcing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Data sharing; Information privacy; The Internet; Encryption; Single point of failure; Mobile device; Data security; Protocol (science); Bloom filter; Secure multi-party computation","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":[0.001194775,0.0005643742,0.0009217941,0.0005346717,0.001179855,0.00123741,0.001811535,0.001368566,0.0007269834],"category_scores_gemma":[0.002992223,0.0002703745,0.0007172094,0.0008704943,0.001475312,0.002935704,0.003315385,0.0009863719,0.0002608703],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009915805,"about_ca_system_score_gemma":0.001268375,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001983498,"about_ca_topic_score_gemma":0.001099491,"domain_scores_codex":[0.9973363,0.0005316195,0.0001663582,0.0005333265,0.001050326,0.0003820849],"domain_scores_gemma":[0.9982771,0.0005312733,0.000256396,0.0005558063,0.0002934905,0.00008589663],"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":[0.001463391,0.0002581129,0.00306127,0.0004684482,0.0001741766,0.001782234,0.001254863,0.4726396,0.1145372,0.1307024,0.003019626,0.2706386],"study_design_scores_gemma":[0.00005087517,0.0002184685,0.0002685469,0.00001851844,0.00003183754,0.0003631381,0.0001567668,0.9359581,0.02775912,0.03123776,0.00388587,0.00005098936],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08451989,0.0004205055,0.9108671,0.0004020083,0.00007598727,0.0001365467,0.00005281586,0.0006185488,0.002906638],"genre_scores_gemma":[0.9572776,0.0001346773,0.04092884,0.00009867288,0.00002604557,0.00006881866,0.00004112066,0.00001990028,0.001404486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001983498,"threshold_uncertainty_score":0.007194459,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01858765233178488,"score_gpt":0.2587873833948896,"score_spread":0.2401997310631047,"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."}}