Assure Information Flows

Dynamic spectrum access (DSA) technique enables wireless devices, called secondary users (SUs), to use spectrum that are allocated to licensed incumbent users (IUs) as long as they do not interfere with IUs' operation. It has been widely accepted as a crucial solution to mitigate the spectrum scarcity problem for wireless communications. As a key form of DSA, regulators have proposed to release more Federal spectrum for sharing with commercial wireless users, under the umbrella of a spectrum access system (SAS) database to govern the spectrum sharing between IUs and SUs.

Medical technologies such as imaging and sequencing make it possible to gather massive amounts of information at increasingly lower cost. Sharing data from studies can advance scientific understanding and improve healthcare outcomes. Concern about patient privacy, however, can preclude open data sharing, thus hampering progress in understanding stigmatized conditions such as mental health disorders.

Language-based security (the use of programming language abstractions and techniques for security) holds the promise of efficient enforcement of strong, formal, fine-grained, application-specific information security guarantees. However, language-based security has not yet reached its potential, and is not in widespread use for providing rich information security guarantees.

This project is developing tools and techniques for cost-effective evaluation of the trustworthiness of mobile applications (apps). The work focuses on enterprise scenarios, in which personnel at a business or government agency use mission-related apps and access enterprise networks.

Many compelling applications involve computations that require sensitive data from two or more individuals. For example, as the cost of personal genome sequencing rapidly plummets many genetics applications will soon be within reach of individuals such as comparing one?s genome with the genomes of different groups of participants in a study to determine which treatment is likely to be most effective. Such comparisons could have tremendous value, but are currently infeasible because of the privacy concerns both for the individual and study participants.