题名 | Blind detection of spread spectrum flow watermarks |
作者 | |
发表日期 | 2009 |
会议名称 | 28th Conference on Computer Communications, IEEE INFOCOM 2009 |
会议录名称 | Proceedings - IEEE INFOCOM
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ISBN | 978-1-4244-3512-8 |
ISSN | 0743-166X |
页码 | 2195-2203 |
会议日期 | APR 19-25, 2009 |
会议地点 | Rio de Janeiro, Brazil |
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 a simple 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 due to 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 and real-world experiments on Tor. Our results demonstrate a high detection rate with a low false positive rate. Our scheme is more flexible and accurate than an existing multi-flow-based approach in DSSS watermark detection. © 2009 IEEE. |
DOI | 10.1109/INFCOM.2009.5062144 |
URL | 查看来源 |
收录类别 | CPCI-S |
语种 | 英语English |
WOS研究方向 | Computer Science ; Engineering ; Telecommunications |
WOS类目 | Computer Science, Hardware & Architecture ; Engineering, Electrical & Electronic ; Telecommunications |
WOS记录号 | WOS:000275366201044 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | https://repository.uic.edu.cn/handle/39GCC9TT/4542 |
专题 | 个人在本单位外知识产出 |
作者单位 | 1.City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong, China 2.Southeast University, Nanjing 210096, China 3.University of Massachusetts, Lowell, MA 01854, United States 4.Ohio-State University, Columbus, OH 43210, United States 5.Cisco Systems, Inc., TX 75082, 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[C], 2009: 2195-2203. |
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