{"id":"W3171733056","doi":"10.1109/tii.2021.3089462","title":"Man-in-the-Middle Attack Mitigation in Internet of Medical Things","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":103,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Man-in-the-middle attack; Computer security; Computer science; Internet of Things; ALARM; Authentication (law); Replay attack; Key (lock); Data transmission; The Internet; Transmission (telecommunications); Real-time computing; Computer network; Engineering; Telecommunications; World Wide Web","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":[0.0009502376,0.0001081212,0.000181753,0.0002065417,0.0000511352,0.0001139318,0.0006961521,0.0002339308,0.00001735813],"category_scores_gemma":[0.00004948286,0.00009395862,0.00007228479,0.0008346124,0.0000446502,0.0006641465,0.000009431873,0.0007512505,0.00002644023],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006703651,"about_ca_system_score_gemma":0.0002430176,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008286856,"about_ca_topic_score_gemma":0.00002204469,"domain_scores_codex":[0.9982073,0.0001058424,0.0007447992,0.0001002799,0.0006260659,0.0002156931],"domain_scores_gemma":[0.9991655,0.0002993984,0.0001351099,0.0002886449,0.00005786114,0.00005348124],"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":[0.0001056277,0.001729272,0.0006283851,0.0003743749,0.0001303871,0.0001957655,0.2392002,0.02820623,0.0000811997,0.005401364,0.0320219,0.6919253],"study_design_scores_gemma":[0.002695904,0.0001825833,0.00009935845,0.0008549124,0.00001479884,0.0001030192,0.002073413,0.9663997,0.01899805,0.000373987,0.007887277,0.0003170467],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.256855,0.00000716772,0.734714,0.001724931,0.005108229,0.0001494292,4.778865e-7,0.00003533,0.001405367],"genre_scores_gemma":[0.9941196,0.00001405484,0.004344116,0.001112747,0.0002811779,0.00001097986,0.000003824049,0.000006371915,0.0001070941],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9381934,"threshold_uncertainty_score":0.3831522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09206165628638721,"score_gpt":0.2886358002534449,"score_spread":0.1965741439670577,"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."}}