{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001345717,0.001234177,0.0009064901,0.0008655876,0.0006569204,0.00113958,0.001021763,0.001312146,0.001805073],"category_scores_gemma":[0.006176664,0.0002978116,0.001167806,0.0004164453,0.001787776,0.002470817,0.003111566,0.001694947,0.0006813204],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005678185,"about_ca_system_score_gemma":0.000631408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007463106,"about_ca_topic_score_gemma":0.0006436093,"domain_scores_codex":[0.9979653,0.0005295335,0.00009972782,0.0004007794,0.0006848623,0.0003197514],"domain_scores_gemma":[0.9972062,0.00108808,0.0003792714,0.0009211172,0.000258076,0.0001473128],"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":[0.000762052,0.0002617746,0.006557594,0.0003146183,0.0002952909,0.000870769,0.0004033839,0.6083138,0.07659818,0.08453982,0.006023753,0.2150591],"study_design_scores_gemma":[0.00003095029,0.0002967686,0.0008036891,0.00003706688,0.00005030065,0.0005393789,0.0000597914,0.9424775,0.0281468,0.0235971,0.003910169,0.00005046455],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0582739,0.0004675102,0.9343485,0.000263738,0.0001109046,0.0001280117,0.00009269516,0.002099652,0.004215092],"genre_scores_gemma":[0.9142873,0.0003106657,0.08181327,0.0003074371,0.0000524082,0.000111581,0.0002543912,0.0002191465,0.002643743],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001805073,"threshold_uncertainty_score":0.007116973,"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."}}