{"id":"W4205705974","doi":"10.3390/drones6010014","title":"Anonymous Mutual and Batch Authentication with Location Privacy of UAV in FANET","year":2022,"lang":"en","type":"article","venue":"Drones","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":25,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Mutual authentication; Drone; Overhead (engineering); Authentication (law); Computer network; Wireless ad hoc network; Vehicular ad hoc network; Mobile ad hoc network; Computer security; Message authentication code; Cryptography; Wireless; Network packet; Telecommunications","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":[0.001502224,0.0004410284,0.0008128316,0.0005916996,0.00119674,0.001315576,0.001308725,0.001044162,0.001389902],"category_scores_gemma":[0.004465185,0.0002011691,0.0006921824,0.0009770818,0.001189857,0.003204681,0.002101217,0.0008066134,0.0003699169],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009065364,"about_ca_system_score_gemma":0.001411935,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001701436,"about_ca_topic_score_gemma":0.001260937,"domain_scores_codex":[0.9970238,0.001060685,0.0002257545,0.0005930801,0.0006287888,0.0004680718],"domain_scores_gemma":[0.9971103,0.0008611544,0.0004483849,0.001063303,0.0003931593,0.0001236786],"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":[0.002261832,0.0002603088,0.004614909,0.0004146876,0.0001501022,0.002119003,0.001566902,0.3924093,0.05198156,0.3833409,0.005722579,0.155158],"study_design_scores_gemma":[0.00005052838,0.0002961248,0.0006777028,0.00002751501,0.00004065059,0.0008641435,0.0002187693,0.9303037,0.01493251,0.04582065,0.006703608,0.00006407801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06143859,0.0003244787,0.9317366,0.0003118839,0.000090521,0.0001764359,0.0001267018,0.0003765599,0.005418236],"genre_scores_gemma":[0.9472463,0.0001857772,0.04811152,0.0000676759,0.00005017681,0.00009604762,0.00009487216,0.00001540617,0.004132265],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001701436,"threshold_uncertainty_score":0.007944643,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.002854105921230097,"score_gpt":0.1621193634928434,"score_spread":0.1592652575716133,"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."}}