{"id":"W2944303438","doi":"10.1145/3310353","title":"Design-Level and Code-Level Security Analysis of IoT Devices","year":2019,"lang":"en","type":"article","venue":"ACM Transactions on Embedded Computing Systems","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Computer security; Internet of Things; Abstraction; Security analysis; Code (set theory); Key (lock); Static analysis; Set (abstract data type); Embedded system","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0007043251,0.0002636244,0.0006098047,0.0007979173,0.0001963229,0.0001233154,0.0009867172,0.0001462402,0.000008727401],"category_scores_gemma":[0.00003482677,0.0002656813,0.0001641902,0.001836123,0.00005348221,0.0002662088,0.00004994662,0.0002748007,0.00001309856],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008952588,"about_ca_system_score_gemma":0.00005235865,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001165554,"about_ca_topic_score_gemma":0.00003471186,"domain_scores_codex":[0.9976945,0.0002608023,0.0006175722,0.0006917313,0.0004240135,0.0003113872],"domain_scores_gemma":[0.9971049,0.0008138694,0.0003799167,0.001351376,0.0002483742,0.0001016059],"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":[0.00009508373,0.0004155857,0.00104561,0.0004790556,0.002332673,0.00001170913,0.00720167,0.8842999,0.007717476,0.004273358,0.00005923962,0.0920686],"study_design_scores_gemma":[0.0004637989,0.0002892924,0.001258833,0.0001623463,0.0002171029,0.00003487458,0.0003936273,0.978354,0.01749916,0.0007500587,0.0001639775,0.0004129569],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.05898933,0.0001047197,0.9392273,0.00005266305,0.0004556535,0.0004912337,0.00004091026,0.000552151,0.00008599531],"genre_scores_gemma":[0.8193428,0.000008649329,0.1804652,0.00005394328,0.00001406905,0.00001584791,0.000001735396,0.00001616016,0.00008161146],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7603535,"threshold_uncertainty_score":0.9999796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.046025044160993,"score_gpt":0.2913326415851101,"score_spread":0.2453075974241171,"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."}}