Research Infrastructure

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.

Online opinions now play a pivotal role in decision making and influence a wide spectrum of our lives. Choices of restaurants at which to dine, places to stay, universities to attend, books to read, doctors to consult, and even political candidates to vote for, are largely influenced by crowdsourced opinions. However, it is estimated that up to 30% of reviews on websites are fake. As a larger part of the US economy is becoming driven by social opinions, it poses a serious risk to the general public (e.g., by getting mislead to invest on low quality products, services or doctors).

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.

As higher education institutions consider moving services to the cloud to save costs and improve collaboration, significant challenges to successful large-scale adoption still exist. Institutions are unwilling to risk cloud deployment because provable technological defenses have thus far been lacking. Control over sensitive data is relinquished without the institution's knowledge, liability is shifted and data breach risks are significantly increased. Further, regulatory-sensitive data has become an increasingly attractive target.

This proposal provides funding for the third GREPSEC: Underrepresented Groups in Security Research workshop, which will held in May 2017, in San Jose CA. This day-and-a-half-long workshop intended for women and underrepresented minorities in computer security and privacy, will be co-located with the IEEE Computer Society's Security and Privacy Symposium, the premier conference in security.