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

2020 IEEE 28th International Conference on Network Protocols (ICNP) Pub Date : 2020-10-13 DOI:10.1109/ICNP49622.2020.9259387

Dongeon Kim, Jihun Han, Jinwoo Lee, Heejun Roh, Wonjun Lee

{"title":"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","authors":"Dongeon Kim, Jihun Han, Jinwoo Lee, Heejun Roh, Wonjun Lee","doi":"10.1109/ICNP49622.2020.9259387","DOIUrl":null,"url":null,"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.","PeriodicalId":233856,"journal":{"name":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Poster: Feasibility of Malware Traffic Analysis through TLS-Encrypted Flow Visualization\",\"authors\":\"Dongeon Kim, Jihun Han, Jinwoo Lee, Heejun Roh, Wonjun Lee\",\"doi\":\"10.1109/ICNP49622.2020.9259387\",\"DOIUrl\":null,\"url\":null,\"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.\",\"PeriodicalId\":233856,\"journal\":{\"name\":\"2020 IEEE 28th International Conference on Network Protocols (ICNP)\",\"volume\":\"33 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 IEEE 28th International Conference on Network Protocols (ICNP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICNP49622.2020.9259387\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 28th International Conference on Network Protocols (ICNP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICNP49622.2020.9259387","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 6

摘要

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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

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

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.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2020 IEEE 28th International Conference on Network Protocols (ICNP)

自引率

0.00%

发文量