{"id":"W4211129876","doi":"10.1109/cns53000.2021.9705050","title":"Context-Aware IoT Device Functionality Extraction from Specifications for Ensuring Consumer Security","year":2021,"lang":"en","type":"article","venue":"","topic":"Access Control and Trust","field":"Social Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Computer science; Vendor; Computer security; Home automation; Access control; Context (archaeology); NIST; Smart device; Confidentiality; Internet of Things; Embedded system; Telecommunications; Human–computer interaction","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":[0.003815545,0.0008071994,0.000522248,0.002350489,0.0008401269,0.002519148,0.001274623,0.001147219,0.003255153],"category_scores_gemma":[0.01420165,0.0009696692,0.002357767,0.0009933581,0.00137689,0.004100095,0.001785697,0.001959516,0.001132783],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001831169,"about_ca_system_score_gemma":0.004474984,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008675181,"about_ca_topic_score_gemma":0.01334037,"domain_scores_codex":[0.9937305,0.001685878,0.0006625637,0.0005611828,0.002980668,0.0003792267],"domain_scores_gemma":[0.9909661,0.0037286,0.0008235874,0.00210882,0.002248046,0.0001248514],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004750719,0.0005002684,0.01691826,0.001788912,0.0002427233,0.003730783,0.004639591,0.2061455,0.08276749,0.4636049,0.0138325,0.205354],"study_design_scores_gemma":[0.00006015843,0.0001544119,0.001784258,0.00056577,0.0002061477,0.00102789,0.0008921161,0.7435877,0.09333318,0.1034354,0.05481687,0.0001361968],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.03589674,0.0001590888,0.952777,0.0005106595,0.0000688345,0.0005717501,0.001328117,0.003508467,0.005179385],"genre_scores_gemma":[0.3936036,0.0003253827,0.5976118,0.0003186583,0.00003704136,0.0005332966,0.003165312,0.0007992778,0.003605571],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.008675181,"threshold_uncertainty_score":0.02017879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1224490786675402,"score_gpt":0.3592713180081955,"score_spread":0.2368222393406553,"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."}}