Internet Censorship detection: A survey

被引:48
作者
Aceto, Giuseppe [1 ]
Pescape, Antonio [1 ,2 ,3 ,4 ,5 ]
机构
[1] Univ Naples Federico II, Dept Elect Engn & Informat Technol, Naples, Italy
[2] Univ Naples Federico II, Course Comp Networks, Naples, Italy
[3] Univ Naples Federico II, Course Comp Architectures, Naples, Italy
[4] Univ Naples Federico II, Course Programming, Naples, Italy
[5] Univ Naples Federico II, Course Multimedia, Naples, Italy
关键词
Internet Censorship; Network monitoring; Communications surveillance; Privacy; Network security; CHINA;
D O I
10.1016/j.comnet.2015.03.008
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Internet Censorship is a phenomenon that crosses several study fields, from computer networking and computer security to social sciences; together with censorship detection and censorship circumvention it has impact on Internet infrastructure, protocols and user behaviors. Detection of Internet Censorship is the basis for the study of this phenomenon, and recently it has received focus from a technical point of view. Due to the heterogeneity of study fields and approaches, the scientific corpus on these topics is still in need of an overall analysis, based on coherent framework and lexicon to describe the experimented approaches and findings. In this paper we present a survey on Internet Censorship detection. We propose a reference for censoring techniques and a characterization of censoring systems, with definitions of related concepts. Based on the censoring techniques investigated in literature, we propose an analysis and discussion of censorship detection techniques and architectures and we present a chronological synopsis of the literature adopting or introducing them. Then we collect, study, and discuss available tools and platforms for censorship detection, and propose a characterization scheme to analyze and compare them. Finally, we compare and discuss detection architectures, tools and platforms, and we use the results to infer current challenges and for proposing new directions in the field of censorship detection. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:381 / 421
页数:41
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