Privacy, theory

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Visible to the public TWC: Medium: Collaborative: Automated Formal Analysis of Security Protocols with Private Coin Tosses

Computerized systems are present in various aspects of modern society. These systems are used to access and share confidential information. Such sharing is achieved through cryptographic protocols which often employ randomization to introduce unpredictability in their behavior to achieve critical security objectives and make it difficult for the malicious adversaries to infer the underlying execution of the participants.

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Visible to the public TWC: Small: PERMIT: Privacy-Enabled Resource Management for IoT Networks

This project investigates how privacy can be used to inform the design and management of future data sensing systems. Networked systems that collect data about individuals will play an increasingly important role in our lives, with applications including industrial monitoring and control, "smart" homes/cities, and personalized health care. These systems will gather private information about individuals, which creates many coupled engineering challenges.

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Visible to the public EAGER: Towards a Better Understanding of Group Privacy in Social Media Community Detection

Much of human communication is now mediated by online social networks. Twitter, Facebook, and Youtube now compete for our collective attention in much the same way as television, radio, and newspapers did for previous generations. But contemporary online social media are qualitatively different from media of the past. Online communication leaves a record of who said what to whom, when, and on what topic.

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Visible to the public CAREER: Sustainable Censorship Resistance Systems for the Next Decade

The Internet enables people around the world to communicate, fostering free speech, a free press, and democracy. For billions of people, however, the freedom to communicate via the Internet is regulated, monitored and restricted by governments or corporations. To combat such censorship, researchers have designed and deployed a variety of censorship circumvention systems. Unfortunately, such systems have been designed based on ad hoc heuristics (rather than on solid, theoretical foundations) and can be defeated by typical state-level censors.

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Visible to the public EAGER: Collaborative: PRICE: Using process tracing to improve household IoT users' privacy decisions

Household Internet-of-Things (IoT) devices are intended to collect information in the home and to communicate with each other, to create powerful new applications that support our day-to-day activities. Existing research suggests that users have a difficult time selecting their privacy settings on such devices. The goal of this project is to investigate how, why and when privacy decisions of household IoT users are suboptimal, and to use the insights from this research to create and test a simple single user interface that integrates privacy settings across all devices within a household.

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Visible to the public TWC: TTP Option: Small: Collaborative: Enhancing Anonymity Network Resilience against Pervasive Internet Attacks

Large-scale Internet censorship prevents citizens of many parts of the world from accessing vast amounts of otherwise publicly available information. The recognition and publication of these censorship events have aided in motivating the development of new privacy-enhancing technologies to circumvent the censor. We argue that as circumvention technologies improve and the cost of detecting their use increases, adversaries that are intent on restricting access to information will seek out alternative techniques for disruption.

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Visible to the public TTP: Small: Collaborative: Defending Against Website Fingerprinting in Tor

The more people use the Internet, the more they risk sharing information they don't want other people to know. Tor is a technology that every day helps millions of people protect their privacy online. Tor users -- ranging from ordinary citizens to companies with valuable intellectual property -- gain protection for the content of their online messages and activities, as well as whom they interact with and when. For the most part, Tor is very secure. However, it has a known vulnerability to an attack called website fingerprinting.

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Visible to the public TWC: Medium: Collaborative: Privacy-Preserving Distributed Storage and Computation

This project aims at developing efficient methods for protecting the privacy of computations on outsourced data in distributed settings. The project addresses the design of an outsourced storage framework where the access pattern observed by the storage server gives no information about the actual data accessed by the client and cannot be correlated with external events. For example, the server cannot determine whether a certain item was previously accessed by the client or whether a certain algorithm is being executed.

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Visible to the public TWC: TTP Option: Frontier: Collaborative: MACS: A Modular Approach to Cloud Security

The goal of the Modular Approach to Cloud Security (MACS) project is to develop methods for building information systems with meaningful multi-layered security guarantees. The modular approach of MACS focuses on systems that are built from smaller and separable functional components, where the security of each component is asserted individually, and where the security of the system as a whole can be derived from the security of its components. The project concentrates on building outsourced, cloud-based information services with client-centric security guarantees.

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Visible to the public NSFSaTC-BSF: TWC: Small: Cryptography and Communication Complexity

Current cloud based systems enable distributed access to both information and computational resources. In this setting, it is imperative to have secure communication, and powerful and expensive cryptographic techniques have been proposed to address this issue. A severely limiting factor, however, is that these methods for securely accessing or processing data between participating parties can result in communication overheads when processing large amounts of data.