{"id":"W4283697320","doi":"10.1109/isqed54688.2022.9806152","title":"Stealthy Attack on Algorithmic-Protected DNNs via Smart Bit Flipping","year":2022,"lang":"en","type":"article","venue":"2022 23rd International Symposium on Quality Electronic Design (ISQED)","topic":"Adversarial Robustness in Machine Learning","field":"Computer Science","cited_by":9,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Simon Fraser University; Government of Canada; CW+","keywords":"Computer science; Robustness (evolution); Deep neural networks; Vulnerability (computing); Adversarial system; Threat model; Computer security; Artificial intelligence; Artificial neural network","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":[0.001095518,0.0009054651,0.0005349212,0.0005267117,0.0004033514,0.0005826451,0.001135696,0.001068747,0.001560638],"category_scores_gemma":[0.005206411,0.0003069276,0.0005370232,0.0002515861,0.001356715,0.001404347,0.001590696,0.001440234,0.0003399359],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000697519,"about_ca_system_score_gemma":0.0005034918,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006259719,"about_ca_topic_score_gemma":0.0007424173,"domain_scores_codex":[0.9990325,0.0002327485,0.00007302903,0.0002008926,0.0003188548,0.0001421049],"domain_scores_gemma":[0.9979668,0.0008926731,0.0002889114,0.0005668793,0.000225893,0.00005886818],"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":[0.0005307517,0.00007625808,0.0026023,0.0002045679,0.0001687134,0.0005612116,0.0002051618,0.7203047,0.0843191,0.05933518,0.00244282,0.1292493],"study_design_scores_gemma":[0.00002152819,0.0001359885,0.0002932647,0.00002897413,0.00003158207,0.000166443,0.00001761761,0.9389561,0.03626416,0.02232418,0.001742044,0.00001802096],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1620298,0.0005520558,0.8285065,0.0005953498,0.0001951679,0.00009348992,0.0001151563,0.001455872,0.006456606],"genre_scores_gemma":[0.9504205,0.0001563426,0.04742732,0.0002617177,0.00002353835,0.00005585443,0.00005673709,0.00006054989,0.001537422],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001560638,"threshold_uncertainty_score":0.00579375,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04025858625416238,"score_gpt":0.3217359100536019,"score_spread":0.2814773237994395,"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."}}