A De-anonymize attack method based on traffic analysis

Ming Song; Gang Xiong; Zhenzhen Li; Junrui Peng; Li Guo

8th International Conference on Communications and Networking in China

Research Article

A De-anonymize attack method based on traffic analysis

Cite: BibTeX Plain Text

@INPROCEEDINGS{10.1109/ChinaCom.2013.6694639,
    author={Ming Song and Gang Xiong and Zhenzhen Li and Junrui Peng and Li Guo},
    title={A De-anonymize attack method based on traffic analysis},
    proceedings={8th International Conference on Communications and Networking in China},
    publisher={IEEE},
    proceedings_a={CHINACOM},
    year={2013},
    month={11},
    keywords={anonymity network tor data mining traffic analysis},
    doi={10.1109/ChinaCom.2013.6694639}
}

Ming Song
Gang Xiong
Zhenzhen Li
Junrui Peng
Li Guo
Year: 2013
A De-anonymize attack method based on traffic analysis
CHINACOM
IEEE
DOI: 10.1109/ChinaCom.2013.6694639

Ming Song¹, Gang Xiong², Zhenzhen Li², Junrui Peng², Li Guo²^,*

1: Beijing University of Posts and Telecommunications
2: Institute of Information Engineering, Chinese Academy of Sciences

*Contact email: guoli@iie.ac.cn

Abstract

While providing protection for users' privacy, anonymity network has also been exploited by criminals to carry out crime anonymously. We study the problem how to break the unlinkability between the senders and recipients in order to identify the source of anonymous traffic in this paper. Tor, the most widely deployed anonymity network, is selected as our target. We develop a de-anonymize attack method based on traffic analysis and choose the {time, stream size} as features for k-means algorithm to mine the association between the first hop traffic and last hop traffic of Tor. Experiments show that our method is effective for Tor.

Keywords: anonymity network tor data mining traffic analysis

Published: 2013-11-14
Publisher: IEEE

: http://dx.doi.org/10.1109/ChinaCom.2013.6694639