Deepflow: Hiding Anonymous Communication Traffic in P2P Streaming Networks

作     者：LV Jianming ZHU Chaoyun TANG Shaohua YANG Can 

作者机构：School of Computer Science and Engineering South China University of Technology 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2014年第19卷第5期

页      面：417-425页

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 0839[工学-网络空间安全] 08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the National Natural Science Foundation of China(61300221) the Fundamental Research Funds for the Central Universities(2014ZZ0038) the Comprehensive Strategic Cooperation Project of Guangdong Province and Chinese Academy of Sciences(2012B090400016) the Technology Planning Project of Guangdong Province(2012A011100005) 

主　　题：anonymity anticensorship Peer-to-Peer streaming 

摘      要：The anonymous communication systems usually have special traffic patterns, which can be detected by censors for further disturbing or blocking. To solve this problem, we present a novel system, Deepflow, to hide anonymous communication traf- fic into the P2P streaming networks such as PPStream by using steganography. Each Deepflow node joins the PPStream network and performs like a normal PPStream client watching a live chan- nel, while embedding communication data into video packets transferred in the network. The steganographed video packets are disseminated by innocuous PPStream clients and reach the target Deepflow node. It is not necessary for Deepflow nodes to link together in the network, which prevents malicious users from sensing IP address of other Deepflow nodes. Deepflow is competent for secret chatting, transferring text documents, or publishing secret bootstrapping information for other anonymous communication systems. Comprehensive experiments in real network environments are conducted in this paper to show the security and efficiency of Deepflow.