Zen-tor:一种零知识已知-未知流量分类方法

Yizhe Gu, Y. Lai, Yipeng Wang
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引用次数: 0

摘要

如今,家庭智能设备被广泛使用,但由于其固有的缺点,如果家庭网络中未知流量过多,恶意流量就会隐藏,那么家庭就可能处于危险之中。提出了一种基于生成对抗网络(GAN)和卷积网络的零知识已知-未知流量分类方法。Zen-tor可以在对未知流量一无所知的情况下,将未知的网络流量与已知的网络流量进行分类,从而训练Zen-tor对只有已知流量的私有家庭网络进行保护。我们在一个公开可用的数据集上对Zen-tor进行了评估,结果表明Zen-tor具有出色的未知分类精度,并且优于最先进的未知流量分类方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Zen-tor: A Zero Knowledge Known-Unknown Traffic Classification Method
Home smart devices are widely used today, but due to their inherent drawbacks, one's home might be in danger if the home network has too many unknown traffic where malicious traffic hides. We present a conceptually new method called Zero Knowledge Known-unknown Traffic Classification(Zen-tor) which utilizes Generative Adversarial Networks(GAN) and con-volutional network. Zen-tor can classify unknown network traffic from known one under the situation of knowing zero knowledge of unknown traffic, thus it can be trained to protect private home network with only known traffic. We evaluate Zen-tor on a publicly available dataset, and the results show that Zen-tor has excellent unknown classification accuracy and outperforms the state-of-the-art unknown traffic classification methods.
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