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Organizational networks are vulnerable to traffic-analysis attacks that enable adversaries to infer sensitive information from the network traffic - even if encryption is used. Typical anonymous communication networks are tailored to the Internet and are poorly suited for organizational networks. We present PriFi, an anonymous communication protocol for LANs, which protects users against eavesdroppers and provides high-performance traffic-analysis resistance. PriFi builds on Dining Cryptographers networks but reduces the high communication latency of prior work via a new client/relay/server architecture, in which a clients packets remain on their usual network path without additional hops, and in which a set of remote servers assist the anonymization process without adding latency. PriFi also solves the challenge of equivocation attacks, which are not addressed by related works, by encrypting the traffic based on the communication history. Our evaluation shows that PriFi introduces a small latency overhead (~100ms for 100 clients) and is compatible with delay-sensitive applications such as VoIP.
With the support of cloud computing, large quantities of data collected from various WSN applications can be managed efficiently. However, maintaining data security and efficiency of data processing in cloud-WSN (C-WSN) are important and challenging
Atom is an anonymous messaging system that protects against traffic-analysis attacks. Unlike many prior systems, each Atom server touches only a small fraction of the total messages routed through the network. As a result, the systems capacity scales
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We introduce Amortized Neural Networks (AmNets), a compute cost- and latency-aware network architecture particularly well-suited for sequence modeling tasks. We apply AmNets to the Recurrent Neural Network Transducer (RNN-T) to reduce compute cost an
Anonymity has become a significant issue in security field by recent advances in information technology and internet. The main objective of anonymity is hiding and concealing entities privacy inside a system. Many methods and protocols have been prop