展示和讲述模式中的闪避攻击

Dongseop Lee, Hyunjin Kim, Jaecheol Ryou
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引用次数: 0

摘要

近年来,深度学习技术以高性能和多种服务被应用于各个领域。通过结合深度学习技术,图像识别也被用于各种高性能领域。然而,深度学习技术很容易受到逃避攻击,这种攻击会导致模型通过调制原始图像而被错误分类。在本文中,我们使用前向后分裂迭代过程生成一个对抗示例。然后对秀秀模特进行闪避攻击。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evasion Attack in Show and Tell Model
Recently, deep learning technology has been applied to various fields with high performance and various services. Image recognition is also used in various fields with high performance by incorporating deep learning technology. However, deep learning technology is vulnerable to evasion attacks that cause the model to be misclassified by modulating the original image. In this paper, we generate an adversarial example using the forward-backward-splitting iterative procedure. Then perform an evasion attack on the show and tell model.
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