{"id":"W3197880668","doi":"10.1109/access.2021.3110239","title":"Use Procedural Noise to Achieve Backdoor Attack","year":2021,"lang":"en","type":"article","venue":"IEEE Access","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Science Foundation of Shaanxi Province; Canadian Institute for Advanced Research","keywords":"Backdoor; Robustness (evolution); Computer science; Computer security; Noise (video); Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":["scholarly_communication"],"consensus_categories":[],"category_scores_codex":[0.0002173706,0.0001973782,0.0002164914,0.00009738357,0.0002227221,0.001101735,0.001976044,0.00007592667,0.00006485177],"category_scores_gemma":[0.0005533541,0.0001946983,0.00007675339,0.001009621,0.00002714197,0.002641628,0.001068241,0.0003679579,0.0003138598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006800153,"about_ca_system_score_gemma":0.0001936591,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00005747163,"about_ca_topic_score_gemma":0.00005679023,"domain_scores_codex":[0.9981245,0.0001558309,0.0002450583,0.0006587864,0.000384814,0.0004310477],"domain_scores_gemma":[0.998409,0.0002205631,0.0000896358,0.0008405397,0.000233217,0.000207101],"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":[0.0002210911,0.000582124,0.0513334,0.0002633076,0.0002075414,0.001880353,0.006050499,0.6769097,0.02220128,0.01678275,0.1124204,0.1111476],"study_design_scores_gemma":[0.003460028,0.0005196126,0.1324061,0.000530843,0.0001082614,0.0005630193,0.0002489027,0.5908333,0.1166196,0.004978262,0.1453079,0.004424215],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2947415,0.00001975308,0.6963055,0.005507386,0.001745102,0.0001952622,0.000002730715,0.000275514,0.00120728],"genre_scores_gemma":[0.9264802,0.000004501394,0.06591333,0.005019184,0.0004046026,0.00002807675,0.000004124282,0.0000293934,0.002116643],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6317387,"threshold_uncertainty_score":0.9999352,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07036943486635322,"score_gpt":0.3503355920491337,"score_spread":0.2799661571827805,"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."}}