{"id":"W3178326529","doi":"10.1145/3460319.3464809","title":"AdvDoor: adversarial backdoor attack of deep learning system","year":2021,"lang":"en","type":"article","venue":"","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":57,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Backdoor; Adversarial system; Computer science; Computer security; Deep learning; Artificial intelligence; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004737358,0.0001906273,0.0003590193,0.00009600243,0.000173971,0.00009217233,0.0008375847,0.0001181023,0.0002646756],"category_scores_gemma":[0.0004173598,0.0001870116,0.0001570306,0.0006511786,0.0000508713,0.0004972936,0.0007916352,0.0004000059,0.0002133944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000941435,"about_ca_system_score_gemma":0.0001340121,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003544631,"about_ca_topic_score_gemma":0.00001308623,"domain_scores_codex":[0.9978266,0.0003566344,0.0004369527,0.0005392915,0.0004775546,0.0003629867],"domain_scores_gemma":[0.9984424,0.0002904357,0.0002271171,0.000658866,0.0002673076,0.0001138425],"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":[0.00005603193,0.0001559063,0.0097779,0.0004496468,0.0002234898,0.0004924712,0.002670751,0.5126298,0.004282319,0.3849261,0.000945021,0.08339056],"study_design_scores_gemma":[0.001303301,0.00009894135,0.001064686,0.00008661774,0.00003242388,0.0001255848,0.001463617,0.9798872,0.004943002,0.0001006853,0.01046422,0.0004296506],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007010167,0.0001390107,0.9462276,0.0002448769,0.001177754,0.00009074535,7.48289e-7,0.000421989,0.04468716],"genre_scores_gemma":[0.8597572,0.000005064655,0.1387784,0.00005980798,0.0001733411,0.000004153067,0.000007210447,0.00001442642,0.001200284],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8527471,"threshold_uncertainty_score":0.7626112,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01220603919960346,"score_gpt":0.2536974820773971,"score_spread":0.2414914428777936,"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."}}