学位论文详细信息
Non-Hierarchical Networks for Censorship-Resistant Personal Communication.
Security;Communication;Ad Hoc Networking;Computer Science;Engineering;Computer Science & Engineering
Bild, David RobinsonFlinn, Jason Nelson ;
University of Michigan
关键词: Security;    Communication;    Ad Hoc Networking;    Computer Science;    Engineering;    Computer Science & Engineering;   
Others  :  https://deepblue.lib.umich.edu/bitstream/handle/2027.42/107314/drbild_1.pdf?sequence=1&isAllowed=y
瑞士|英语
来源: The Illinois Digital Environment for Access to Learning and Scholarship
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【 摘 要 】

The Internet promises widespread access to the world’s collective information and fast communication among people, but common government censorship and spying undermines this potential. This censorship is facilitated by the Internet’s hierarchical structure. Most traffic flows through routers owned by a small number of ISPs, who can be secretly coerced into aiding such efforts. Traditional crypographic defenses are confusing to common users. This thesis advocates direct removal of the underlying heirarchical infrastructure instead, replacing it with non-hierarchical networks. These networks lack such chokepoints, instead requiring would-be censors to control a substantial fraction of the participating devices—an expensive proposition. We take four steps towards the development of practical non-hierarchical networks. (1) We first describe Whisper, a non-hierarchical mobile ad hoc network (MANET) architecture for personal communication among friends and familythat resists censorship and surveillance. At its core are two novel techniques, an efficient routing scheme based on the predictability of human locations anda variant of onion-routing suitable for decentralized MANETs. (2) We describe the design and implementation of Shout, a MANET architecture for censorship-resistant, Twitter-like public microblogging. (3) We describe the Mason test, amethod used to detect Sybil attacks in ad hoc networks in which trusted authorities are not available. (4) We characterize and model the aggregate behavior of Twitter users to enable simulation-based study of systems like Shout. We use our characterization of the retweet graph to analyze a novel spammer detection technique for Shout.

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