{"id":"W4385327837","doi":"10.48550/arxiv.2307.13952","title":"Security Weaknesses in IoT Management Platforms","year":2023,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Internet of Things; Computer security; Computer science; Authentication (law); Key (lock); Set (abstract data type); World Wide Web","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002012696,0.0005347339,0.000263548,0.001930522,0.001033594,0.00159158,0.0006966896,0.0009351679,0.0008861691],"category_scores_gemma":[0.01079351,0.0003401906,0.0004688869,0.0009584926,0.001438408,0.003057067,0.001790627,0.0008271202,0.0002108157],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009644378,"about_ca_system_score_gemma":0.0009101216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00116386,"about_ca_topic_score_gemma":0.001086649,"domain_scores_codex":[0.997447,0.0004829807,0.0001927615,0.0003467072,0.001134251,0.0003962833],"domain_scores_gemma":[0.9931445,0.002466913,0.001868873,0.001407135,0.0009225576,0.0001900618],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001334133,0.0006520702,0.4384405,0.001264911,0.0002784829,0.006966947,0.01043963,0.05919849,0.1358527,0.07694893,0.008891976,0.2597313],"study_design_scores_gemma":[0.00007857203,0.001626597,0.238663,0.001485186,0.0006522121,0.01212985,0.0112809,0.4539974,0.1778809,0.05494063,0.04696948,0.0002951791],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748034,0.0003327748,0.01410753,0.0003984138,0.00003379884,0.000189858,0.0001422817,0.0003758823,0.009616046],"genre_scores_gemma":[0.9926484,0.0001152029,0.006376998,0.00007362026,0.000006817203,0.00005019494,0.00009419255,0.00002879727,0.0006058026],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002012696,"threshold_uncertainty_score":0.01064432,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07250214041342248,"score_gpt":0.2023674064683704,"score_spread":0.1298652660549479,"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."}}