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A Scalable and Privacy-Preserving Named Data Networking Architecture Based on Bloom Filters

机译:基于布隆过滤器的可扩展且保留隐私的命名数据网络体系结构

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Currently, there are numbers of different architectural proposals for future internet that focus on content-centric networking as the alternative of the existing location-based networking. These architectures give more emphasis on the security part of their paradigms and pay little attention or ignore on issues of privacy in their architectural designs. In this paper we propose the Scalable and Privacy Preserving Routing Protocol in Named Data Networking (SP-NDN) by utilizing the multiple Bloom filters in order to ameliorate user's interest packet flow privacy and security during the transit. In contrast to existing schemes, we present a content-dependent key tree based on multicast key management protocol to integrate Bloom filter and multicast encryption that mitigates the leakage of the original user's keywords and precluding unauthorized users (eavesdroppers) from guessing the key words. Our schemes guarantee the high security and privacy of user's interest packet during the transmission and at the same time trying to minimize the possible increase number of false positives likely to happen when a content is queried.
机译:当前,针对未来的互联网有许多不同的体系结构提案,这些提案专注于以内容为中心的网络,以替代现有的基于位置的网络。这些体系结构更加注重其范式的安全性,而很少关注或忽略其体系结构设计中的隐私问题。在本文中,我们提出了利用多个布隆过滤器的命名数据网络(SP-NDN)中的可伸缩性和隐私保留路由协议,以改善传输过程中用户的兴趣数据包流的隐私性和安全性。与现有方案相比,我们提出了一种基于内容的密钥树,该密钥树基于多播密钥管理协议,以集成Bloom筛选器和多播加密,从而减轻了原始用户关键字的泄漏,并防止未经授权的用户(窃听者)猜测关键字。我们的方案在传输过程中保证了用户兴趣包的高度安全性和私密性,同时试图最大程度地减少查询内容时可能出现的误报的数量。

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