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De Cristofaro E.,PARC | Soriente C.,ETH Zurich | Tsudik G.,University of California at Irvine | Williams A.,University of California at Irvine
Proceedings - IEEE Symposium on Security and Privacy | Year: 2012

In the last several years, micro-blogging Online Social Networks (OSNs), such as Twitter, have taken the world by storm, now boasting over 100 million subscribers. As an unparalleled stage for an enormous audience, they offer fast and reliable centralized diffusion of pithy tweets to great multitudes of information-hungry and always-connected followers. At the same time, this information gathering and dissemination paradigm prompts some important privacy concerns about relationships between tweeters, followers and interests of the latter. In this paper, we assess privacy in today's Twitter-like OSNs and describe an architecture and a trial implementation of a privacy-preserving service called Hummingbird. It is essentially a variant of Twitter that protects tweet contents, hash tags and follower interests from the (potentially) prying eyes of the centralized server. We argue that, although inherently limited by Twitter's mission of scalable information-sharing, this degree of privacy is valuable. We demonstrate, via a working prototype, that Hummingbird's additional costs are tolerably low. We also sketch out some viable enhancements that might offer better privacy in the long term. © 2012 IEEE.

Blundo C.,University of Salerno | De Cristofaro E.,PARC | Gasti P.,University of California at Irvine
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2013

In today's digital society, electronic information is increasingly shared among different entities, and decisions are made based on common attributes. To address associated privacy concerns, the research community has begun to develop cryptographic techniques for controlled (privacy-preserving) information sharing. One interesting open problem involves two mutually distrustful parties that need to assess the similarity of their information sets, but cannot disclose their actual content. This paper presents the first efficient and provably-secure construction for privacy-preserving evaluation of sample set similarity, measured as the Jaccard similarity index. We present two protocols: the first securely computes the Jaccard index of two sets, the second approximates it, using MinHash techniques, with lower costs. We show that our novel protocols are attractive in many compelling applications, including document similarity, biometric authentication, genetic tests, multimedia file similarity. Finally, we demonstrate that our constructions are appreciably more efficient than prior work. © 2013 Springer-Verlag.

Nichols K.,Pollere, Inc. | Jacobson V.,PARC
Communications of the ACM | Year: 2012

The article aims to provide part of the buffer bloat solution, proposing an innovative approach to AQM suitable for today's Internet called CoDel. Packet networks require buffers to absorb short-term arrival rate fluctuations. Although essential to the operation of packet networks, buffers tend to fill up and remain full at congested links, contributing to excessive traffic delay and losing the ability to perform their intended function of absorbing bursts. The Internet has been saved from disaster by a constant increase in link rates and by usage patterns. Over the past decade, evidence has accumulated that this whistling in the dark cannot continue without severely impacting Internet usage. Developing effective active queue management has been hampered by misconceptions about the cause and meaning of queues. Network buffers exist to absorb the packet bursts that occur naturally in statistically multiplexed networks.

De Cristofaro E.,PARC | Tsudik G.,University of California at Irvine
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Year: 2012

Private Set Intersection (PSI) is a useful cryptographic primitive that allows two parties (client and server) to interact based on their respective (private) input sets, in such a way that client obtains nothing other than the set intersection, while server learns nothing beyond client set size. This paper considers one PSI construct from [DT10] and reports on its optimized implementation and performance evaluation. Several key implementation choices that significantly impact real-life performance are identified and a comprehensive experimental analysis (including micro-benchmarking, with various input sizes) is presented. Finally, it is shown that our optimized implementation of this RSA-OPRF-based PSI protocol markedly outperforms the one presented in [HEK12]. © 2012 Springer-Verlag.

Stefik M.,PARC | Good L.,Google
AI Magazine | Year: 2012

From 2008-2010 we built an experimental personalized news system where readers subscribed to organized channels of topical information that were curated by experts. AI technology was employed to present the right information efficiently to each reader and to reduce radically the workload of curators. The system went through three implementation cycles and processed more than 20 million news stories from about 12,000 Really Simple Syndication (RSS) feeds on more than 8000 topics organized by 160 curators for more than 600 registered readers. This article describes the approach, engineering, and AI technology of the system. Copyright © 2012 Association for the Advancement of Artificial Intelligence. All rights reserved.

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