{"id":"W4392942157","doi":"10.1109/icmla58977.2023.00216","title":"Towards Augmentation Based Defense Strategies Against Adversarial Attacks","year":2023,"lang":"en","type":"article","venue":"","topic":"Advanced Malware Detection Techniques","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Adversarial system; Computer science; Computer security; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001795524,0.001311041,0.00103856,0.0008586977,0.0004923642,0.001095405,0.0013661,0.001743547,0.002071519],"category_scores_gemma":[0.005134308,0.0004747511,0.0005295312,0.0003018352,0.001689727,0.002504399,0.002989137,0.003123953,0.001023601],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006108836,"about_ca_system_score_gemma":0.0005890173,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004190926,"about_ca_topic_score_gemma":0.0004304475,"domain_scores_codex":[0.9989537,0.0002904235,0.00003796383,0.0001725596,0.0003736027,0.0001717793],"domain_scores_gemma":[0.9969896,0.001454242,0.0002902051,0.0006631771,0.0004284779,0.0001742973],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0003485802,0.0002920089,0.002095856,0.0002206074,0.0001020054,0.0002657169,0.0002668289,0.535952,0.06204933,0.1287022,0.01216117,0.2575436],"study_design_scores_gemma":[0.000009590178,0.00009275183,0.00014771,0.00002039565,0.00001078327,0.0001213964,0.00002015836,0.9597431,0.005821116,0.03053895,0.003462743,0.00001113603],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03971723,0.001450597,0.9450524,0.001354595,0.0002129529,0.0001209866,0.00005899958,0.002027612,0.01000459],"genre_scores_gemma":[0.8275937,0.0007259735,0.1642744,0.001071895,0.0002313944,0.0001615711,0.0001476837,0.0001690137,0.005624401],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002071519,"threshold_uncertainty_score":0.009495795,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02149410332537222,"score_gpt":0.2988847114398802,"score_spread":0.2773906081145079,"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."}}