Poster: Feasibility of Malware Traffic Analysis through TLS-Encrypted Flow Visualization

Dongeon Kim, Jihun Han, Jinwoo Lee, Heejun Roh, Wonjun Lee
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引用次数: 6

Abstract

With the wide adoption of TLS, malware’s use of TLS is also growing fast. However, fine-grained feature selection in existing approaches is too burdensome. To this end, we propose to visualize TLS-encrypted flow metadata as an image for better malware traffic analysis and classification. We discuss its feasibility and show some preliminary classification results with high accuracy.
海报:通过tls加密流可视化进行恶意软件流量分析的可行性
随着TLS的广泛采用,恶意软件对TLS的使用也在快速增长。然而,现有方法中的细粒度特征选择过于繁琐。为此,我们建议将tls加密的流量元数据可视化为图像,以便更好地进行恶意软件流量分析和分类。讨论了该方法的可行性,并给出了一些具有较高准确率的初步分类结果。
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