Traffic Pattern Plot: Video Identification in Encrypted Network Traffic

被引：0

作者：

Kamal, Ali S. ^{[1
]}

Bukhari, Syed M. A. H. ^{[1
]}

Khan, Muhammad U. S. ^{[1
]}

Maqsood, Tahir ^{[1
]}

Fayyaz, Muhammad A. B. ^{[2
]}

机构：

[1] COMSATS Univ Islamabad, Dept Comp Sci, Abbottabad, Pakistan

[2] Manchester Metropolitan Univ Manchester, OTEHM, Manchester, Lancs, England

来源：

INTELLIGENT SUSTAINABLE SYSTEMS, WORLDS4 2022, VOL 2 | 2023年 / 579卷

关键词：

Traffic pattern; VPN traffic classification; YouTube video identification; Image classification; NEURAL-NETWORKS; CLASSIFICATION; INTERNET;

D O I：

10.1007/978-981-19-7663-6_8

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Most of the Internet traffic is encrypted, and the challenge is its ability to recognize the streaming videos from the Internet traffic. In this paper, we present a methodology named traffic pattern plot (TPP) to identify video streams in encrypted network traffic. The proposed methodology plots the video traffic flows and uses a convolutional neural network (CNN) to detect the videos. The results show that the traffic pattern plot generated from 120 s of sniffing network traffic is enough to identify the video even in the encrypted network traffic with 94% accuracy.

引用

页码：77 / 84

页数：8

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