{"id":"W3133856821","doi":"10.1109/ivworkshops54471.2021.9669214","title":"Cybersecurity Threats in Connected and Automated Vehicles based Federated Learning Systems","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Privacy-Preserving Technologies in Data","field":"Computer Science","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Computer science; Computer network; Wireless network; Resilience (materials science); Process (computing); Wireless; Node (physics); Computer security; Distributed computing; Telecommunications; Engineering","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":[0.002275052,0.000475483,0.0006384258,0.0007172153,0.0009340442,0.001881492,0.001059888,0.001669159,0.00060113],"category_scores_gemma":[0.008419372,0.000232022,0.00056243,0.0006000909,0.00171087,0.002953221,0.002454606,0.000998605,0.0001100385],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00148955,"about_ca_system_score_gemma":0.001021731,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001904852,"about_ca_topic_score_gemma":0.0008077571,"domain_scores_codex":[0.9978397,0.0008389672,0.0001214873,0.000303588,0.0005757947,0.0003204276],"domain_scores_gemma":[0.9941299,0.003147634,0.0007593963,0.001172271,0.0005681729,0.0002227175],"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":[0.0002535401,0.0001157742,0.006593057,0.00006275481,0.0001049047,0.0004948359,0.0004210144,0.890335,0.003660952,0.05513109,0.0007936008,0.04203348],"study_design_scores_gemma":[0.00001203447,0.000097212,0.000599961,0.00001497953,0.00001378941,0.0001523573,0.0001282039,0.9668686,0.003541256,0.02749919,0.001061884,0.00001050096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5235828,0.000362329,0.4700486,0.0009408176,0.00006391839,0.000122618,0.00007530824,0.0007359737,0.004067713],"genre_scores_gemma":[0.9931172,0.00004916647,0.006392075,0.00004332566,0.000005582281,0.00001404065,0.00002140609,0.000006004245,0.0003511216],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002275052,"threshold_uncertainty_score":0.01203173,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0349031543724486,"score_gpt":0.2828926180624777,"score_spread":0.2479894636900291,"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."}}