{"id":"W4393956373","doi":"10.1145/3603166.3632551","title":"Trust Evaluation in IoT Systems: Extracting User Trust Levels based on Security Profiles in Water Treatment Facilities","year":2023,"lang":"en","type":"article","venue":"","topic":"Network Security and Intrusion Detection","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Sherbrooke","funders":"","keywords":"Internet of Things; Computer science; Computer security; Trust management (information system)","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":[0.001845301,0.0004475999,0.0004491643,0.001719281,0.0005682603,0.001465322,0.0003403648,0.0005185953,0.0004884471],"category_scores_gemma":[0.01167725,0.0001692827,0.0004916919,0.001200807,0.0003290856,0.001687858,0.0009678085,0.0005122137,0.0002416248],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000930067,"about_ca_system_score_gemma":0.0005059507,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005602463,"about_ca_topic_score_gemma":0.006646818,"domain_scores_codex":[0.9982156,0.0006662837,0.000261086,0.0002107177,0.0004333842,0.0002130036],"domain_scores_gemma":[0.9934421,0.002487286,0.001682098,0.0004828091,0.001452518,0.0004531282],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001779277,0.000845011,0.7919773,0.0004468784,0.0003864944,0.0006321095,0.00595645,0.02632118,0.01912241,0.002190839,0.001601109,0.1487408],"study_design_scores_gemma":[0.00003516713,0.001177079,0.5112092,0.0001387441,0.0002740135,0.0005815055,0.008142676,0.4554151,0.01490266,0.005695281,0.002298851,0.0001297882],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9650055,0.0001145887,0.03273537,0.0001101197,0.000008347519,0.00008366164,0.0002662656,0.00008910909,0.001587032],"genre_scores_gemma":[0.9970337,0.00001895468,0.002692193,0.0000059271,0.00000155374,0.00001689139,0.0001123207,0.000002923904,0.000115529],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005602463,"threshold_uncertainty_score":0.01113969,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05906214480149323,"score_gpt":0.2880550071911269,"score_spread":0.2289928623896337,"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."}}