Honglu He, Zhiying Zhu, Xinpeng Zhang*
CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.3, pp. 2617-2633, 2023, DOI:10.32604/cmes.2023.025923
Abstract In recent years, the number of parameters of deep neural networks (DNNs) has been increasing rapidly. The training
of DNNs is typically computation-intensive. As a result, many users leverage cloud computing and outsource their
training procedures. Outsourcing computation results in a potential risk called backdoor attack, in which a welltrained DNN would perform abnormally on inputs with a certain trigger. Backdoor attacks can also be classified as
attacks that exploit fake images. However, most backdoor attacks design a uniform trigger for all images, which can
be easily detected and removed. In this paper, we propose a novel adaptive backdoor attack.… More >
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