{"id":"W4400350652","doi":"10.3390/electronics13132646","title":"Mitigating Adversarial Attacks against IoT Profiling","year":2024,"lang":"en","type":"article","venue":"Electronics","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Profiling (computer programming); Computer science; Adversarial system; Hyperparameter; Internet of Things; Deep learning; Machine learning; Artificial intelligence; Computer security","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":[0.003005033,0.001214508,0.000833768,0.000695653,0.0006099528,0.000779443,0.001000749,0.001071702,0.0007484711],"category_scores_gemma":[0.01216905,0.0003197317,0.0006273617,0.0003744888,0.001054253,0.002080981,0.002307153,0.002124765,0.000433647],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006589335,"about_ca_system_score_gemma":0.0006717098,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001238295,"about_ca_topic_score_gemma":0.001659199,"domain_scores_codex":[0.9982167,0.0007621954,0.00008084274,0.0002682589,0.000428589,0.0002433629],"domain_scores_gemma":[0.9932458,0.003632814,0.0007624686,0.001654624,0.0005174205,0.0001868726],"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":[0.0008270368,0.0004121675,0.009332445,0.0001352955,0.0001375751,0.0003306073,0.0002084106,0.8217039,0.02255639,0.005587571,0.004588647,0.13418],"study_design_scores_gemma":[0.000008862066,0.00009738874,0.0007356681,0.00001553273,0.0000117904,0.00008216831,0.0000285325,0.9876989,0.008308727,0.002537698,0.0004653605,0.000009298072],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4209723,0.0008540845,0.5685056,0.001180075,0.0002214971,0.0002137342,0.000333736,0.003661845,0.00405711],"genre_scores_gemma":[0.9495544,0.0001296673,0.04850178,0.0003120472,0.00004389352,0.00005728934,0.0003189378,0.00009325852,0.0009886858],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003005033,"threshold_uncertainty_score":0.01589227,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008803132866681412,"score_gpt":0.268568470802995,"score_spread":0.2597653379363136,"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."}}