{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/query-limited-black-box-attacks-to","title":"Query-limited Black-box Attacks to Classifiers","arxiv_id":"1712.08713","date":"2017-12-23","proceeding":null,"authors":["Fnu Suya","Yuan Tian","David Evans","Paolo Papotti"],"abstract":"We study black-box attacks on machine learning classifiers where each query\nto the model incurs some cost or risk of detection to the adversary. We focus\nexplicitly on minimizing the number of queries as a major objective.\nSpecifically, we consider the problem of attacking machine learning classifiers\nsubject to a budget of feature modification cost while minimizing the number of\nqueries, where each query returns only a class and confidence score. We\ndescribe an approach that uses Bayesian optimization to minimize the number of\nqueries, and find that the number of queries can be reduced to approximately\none tenth of the number needed through a random strategy for scenarios where\nthe feature modification cost budget is low.","url_abs":"http://arxiv.org/abs/1712.08713v1","url_pdf":"http://arxiv.org/pdf/1712.08713v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"query-limited-black-box-attacks-to","repo_url":"https://github.com/suyeecav/Bayesian-Optimization-for-Classifier-Evasion","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"machine-learning","task_name":"BIG-bench Machine Learning"},{"task_slug":"bayesian-optimization","task_name":"Bayesian Optimization"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1712.08713","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}