A Survey on Tor Encrypted Traffic Monitoring

被引:0
|
作者
Aminuddin, Mohamad Amar Irsyad Mohd [1 ]
Zaaba, Zarul Fitri [1 ]
Singh, Manmeet Kaur Mahinderjit [1 ]
Singh, Darshan Singh Mahinder [2 ]
机构
[1] Univ Sains Malaysia, Sch Comp Sci, Usm 11800, Pulau Pinang, Malaysia
[2] Univ Sains Malaysia, Sch Comp Sci, Ctr Drug Res, Usm 11800, Pulau Pinang, Malaysia
关键词
Encrypted traffic monitoring; Tor; machine learning; security; survey;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Tor (The Onion Router) is an anonymity tool that is widely used worldwide. Tor protect its user privacy against surveillance and censorship using strong encryption and obfuscation techniques which makes it extremely difficult to monitor and identify users' activity on the Tor network. It also implements strong defense to protect the users against traffic features extraction and website fingerprinting. However, the strong anonymity also became the heaven for criminal to avoid network tracing. Therefore, numerous of research has been performed on encrypted traffic analyzing and classification using machine learning techniques. This paper presents survey on existing approaches for classification of Tor and other encrypted traffic. There is preliminary discussion on machine learning approaches and Tor network. Next, there are comparison of the surveyed traffic classification and discussion on their classification properties.
引用
收藏
页码:113 / 120
页数:8
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