{"id":"W3024606024","doi":"10.1109/access.2020.2993553","title":"Attacks and Defenses in Short-Range Wireless Technologies for IoT","year":2020,"lang":"en","type":"article","venue":"IEEE Access","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":126,"is_retracted":false,"has_abstract":true,"ca_institutions":"Queen's University","funders":"Division of Electrical, Communications and Cyber Systems; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Wireless; Computer science; Internet of Things; Range (aeronautics); Computer security; Computer network; Telecommunications; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001144295,0.0008826883,0.0008151485,0.002096928,0.001137334,0.002456755,0.0007603992,0.002238767,0.0009737246],"category_scores_gemma":[0.003954945,0.0004074665,0.000718103,0.001574382,0.001909057,0.00493149,0.001518358,0.002488861,0.0003777948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008615481,"about_ca_system_score_gemma":0.0005626329,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004960634,"about_ca_topic_score_gemma":0.0003455576,"domain_scores_codex":[0.9977112,0.000639417,0.0001434617,0.0001937872,0.001079403,0.0002327725],"domain_scores_gemma":[0.997349,0.001461769,0.0004349565,0.0003093323,0.00034906,0.00009590734],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001651879,0.0002210969,0.004598652,0.0008985049,0.0001256928,0.0009549132,0.0008261926,0.05722604,0.01520051,0.5995414,0.01248285,0.3077589],"study_design_scores_gemma":[0.00003380676,0.0005541195,0.004228722,0.001127333,0.0001377142,0.00461859,0.00114291,0.4425875,0.01391018,0.3915467,0.1399705,0.0001419488],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06078822,0.119522,0.7511176,0.009093863,0.001372631,0.0004236295,0.0001295088,0.000968691,0.05658393],"genre_scores_gemma":[0.8056697,0.07251767,0.1063279,0.001783466,0.001681438,0.0004683432,0.0002260753,0.00009173033,0.01123373],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002456755,"threshold_uncertainty_score":0.006251037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06158950359987024,"score_gpt":0.3357675878411083,"score_spread":0.2741780842412381,"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."}}