Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models
Abstract
Deep Neural Networks (DNNs) are vulnerable to deliberately crafted adversarial examples. In the past few years, many efforts have been spent on exploring query-optimisation attacks to find adversarial examples of either black-box or white-box DNN models, as well as the defending countermeasures against those attacks. In this work, we explore vulnerabilities of DNN models under the umbrella of Man-in-the-Middle (MitM) attacks, which has not been...
Paper Details
Title
Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models
Published Date
Oct 14, 2019
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