Privacy, applied

group_project

Visible to the public TWC: Frontier: Collaborative: CORE: Center for Encrypted Functionalities

Submitted by Susan Hohenberger on Mon, 10/23/2017 - 2:57pm

The Center for Encrypted Functionalities (CORE) tackles the deep and far-reaching problem of general-purpose "program obfuscation," which aims to enhance cybersecurity by making an arbitrary computer program unintelligible while preserving its functionality.

group_project

Visible to the public CAREER: Contextual Protection for Private Data Storage and Retrieval

Submitted by Christopher Kanich on Wed, 10/18/2017 - 7:26pm

This research is building an understanding of what data is useful to attackers and what data is private for its legitimate owners so that security systems can incorporate these values into a data-driven, defense-in-depth approach to securing our digital lives. We are exploiting the fact that both users and attackers must sift through vast amounts of data to find useful information.

group_project

Visible to the public TWC SBE: Small: From Threat to Boon: Understanding and Controlling Strategic Information Transmission in Cyber-Socio-Physical Systems

Submitted by Cedric Langbort on Wed, 10/18/2017 - 6:05pm

As cyber-socio-physical and infrastructure systems are increasingly relying on data and integrating an ever-growing range of disparate, sometimes unconventional, and possibly untrusted data sources, there is a growing need to consider the problem of estimation in the presence of strategic and/or self-interested sensors. This class of problems, called "strategic information transmission" (SIT), differs from classical fault-tolerant estimation since the sensors are not merely failing or malfunctioning, but are actively trying to mislead the estimator for their own benefit.

group_project

Visible to the public TWC: Medium: Collaborative: Broker Leads for Privacy-Preserving Discovery in Health Information Exchange

Submitted by Carl Gunter on Wed, 10/18/2017 - 3:18pm

Support for research on distributed data sets is challenged by stakeholder requirements limiting sharing. Researchers need early stage access to determine whether data sets are likely to contain the data they need. The Broker Leads project is developing privacy-enhancing technologies adapted to this discovery phase of data-driven research. Its approach is inspired by health information exchanges that are based on a broker system where data are held by healthcare providers and collected in distributed queries managed by the broker.

group_project

Visible to the public SBE TWC: Small: Collaborative: Privacy Protection in Social Networks: Bridging the Gap Between User Perception and Privacy Enforcement

Submitted by Bo Luo on Wed, 10/18/2017 - 1:29pm

Online social networks, such as Facebook, Twitter, and Google+, have become extremely popular. They have significantly changed our behaviors for sharing information and socializing, especially among the younger generation. However, the extreme popularity of such online social networks has become a double-edged sword -- while promoting online socialization, these systems also raise privacy issues.

group_project

Visible to the public TWC: Medium: Collaborative: Development and Evaluation of Next Generation Homomorphic Encryption Schemes

Submitted by Berk Sunar on Tue, 10/17/2017 - 5:37pm

Fully homomorphic encryption (FHE) is a promising new technology that enables an untrusted party to efficiently compute directly on ciphertexts. For instance, with FHE a cloud server without access to the user's encrypted content can still provide text search services. An efficient FHE scheme would significantly improve the security of sensitive user data stored and processed on cloud servers. Significant progress has been made in bringing FHE proposals closer to practice.

group_project

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

Submitted by Bart Knijnenburg on Tue, 10/17/2017 - 1:54pm

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.

group_project

Visible to the public TWC: Medium: Collaborative: Re[DP]: Realistic Data Mining Under Differential Privacy

Submitted by mvnak on Mon, 10/16/2017 - 5:35pm

The collection and analysis of personal data about individuals has revolutionized information systems and fueled US and global economies. But privacy concerns regarding the use of such data loom large. Differential privacy has emerged as a gold standard for mathematically characterizing the privacy risks of algorithms using personal data. Yet, adoption of differentially private algorithms in industry or government agencies has been startlingly rare.

group_project

Visible to the public CAREER: PROTEUS: A Practical and Rigorous Toolkit for Privacy

Submitted by mvnak on Mon, 10/16/2017 - 5:31pm

Statistical privacy, or the problem of disclosing aggregate statistics about data collected from individuals while ensuring the privacy of individual level sensitive properties, is an important problem in today's age of big data. The key challenge in statistical privacy is that applications for data collection and analysis operate on varied kinds of data, and have diverse requirements for the information that must be kept secret, and the adversaries that they must tolerate.