发表状态 | 已发表Published |
题名 | Blind detection of spread spectrum flow watermarks |
作者 | |
发表日期 | 2013 |
发表期刊 | Security and Communication Networks
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ISSN/eISSN | 1939-0114 |
卷号 | 6期号:3页码:257-274 |
摘要 | Recently, the direct sequence spread spectrum (DSSS)-based technique has been proposed to trace anonymous network flows. In this technique, homogeneous pseudo-noise (PN) codes are used to modulate multiple bit signals that are embedded into the target flow as watermarks. This technique could be maliciously used to degrade an anonymous communication network. In this paper, we propose an effective single flow-based scheme to detect the existence of these watermarks. Our investigation shows that, even if we have no knowledge of the applied PN code, we are still able to detect malicious DSSS watermarks via mean-square autocorrelation (MSAC) of a single modulated flow's traffic rate time series. MSAC shows periodic peaks because of self-similarity in the modulated traffic caused by homogeneous PN codes that are used in modulating multiple bit signals. Our scheme has low complexity and does not require any PN code synchronization. We evaluate this detection scheme's effectiveness via simulations. Our results demonstrate a high detection rate with a low false positive rate. Real-world experiments on Tor also validate the feasibility of the detection scheme. Our scheme is more flexible and accurate than the existing multiflow-based approach in DSSS watermark detection. We also present a theory for reconstructing the DSSS code once the DSSS code length is known and simulations validate the feasibility. © 2012 John Wiley & Sons, Ltd. |
关键词 | Anonymity Detection DSSS Mean-square autocorrelation |
DOI | 10.1002/sec.540 |
URL | 查看来源 |
收录类别 | SCIE |
语种 | 英语English |
WOS研究方向 | Computer Science ; Telecommunications |
WOS类目 | Computer Science, Information Systems ; Telecommunications |
WOS记录号 | WOS:000315405700002 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/1906 |
专题 | 个人在本单位外知识产出 |
作者单位 | 1.City University of Hong Kong, Kowloon, Tat Chee Avenue, Hong Kong, China 2.School of Computer Science and Engineering, Southeast University, Nanjing, 210096, Liwenzheng Building (North) #241, China 3.Department of Computer Science, University of Massachusetts Lowell, Lowell, MA, 01854, United States 4.Department of Computer Science and Engineering, The Ohio State University, Columbus, OH, 43210, United States 5.Department of Computer and Information Sciences, Towson University, Towson, MD, United States |
推荐引用方式 GB/T 7714 | Jia, Weijia,Tso, Fung Po,Ling, Zhenet al. Blind detection of spread spectrum flow watermarks[J]. Security and Communication Networks, 2013, 6(3): 257-274. |
APA | Jia, Weijia, Tso, Fung Po, Ling, Zhen, Fu, Xinwen, Xuan, Dong, & Yu, Wei. (2013). Blind detection of spread spectrum flow watermarks. Security and Communication Networks, 6(3), 257-274. |
MLA | Jia, Weijia,et al."Blind detection of spread spectrum flow watermarks". Security and Communication Networks 6.3(2013): 257-274. |
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