Ran Wang1, Haopeng Ke2, Meng Hu3

  • 1School of Mathematical Science, Shenzhen University, Shenzhen, 518060, China; Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, 518060, China; Shenzhen Key Laboratory of Advanced Machine Learning and Applications, Shenzhen University, Shenzhen, 518060, China.

概括

本研究介绍了Margin-SNN,这是一种使用随机神经网络 (SNN) 来增强深度神经网络 (DNN) 的对抗性强度的新型防御方法. 边缘-SNN通过学习特征不确定性和嵌入标签来提高阶级分离的性能来提高安全性,优于标准对抗训练.

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