Areas of Research

Our research covers a wide range of topics that are essential to enable the development of technology that can be used to build socially responsible systems. These are our main lines of research (see our publications page for more details)

Engineering privacy-preserving systems

The awareness of users about the invasive nature of many on-line services and mobile devices in our daily lives has put Privacy Technologies in the spotlight. While the need for privacy is undisputed, how to design and deploy privacy-preserving systems is not well undersood, hindering the development of solutions that enable society to enjoy technological progress without damaging our societal values.

At the SPRING Lab we work on developing building blocks that engineers can use to build privacy-preserving systems, and methodologies that allow them to reason in a systematic manner both about the design and the evaluation of privacy-preserving technologies.

Related publications:

Impact of Machine learning

At the SPRING Lab we try to understand the impact of machine learning on society, and how it changes security and privacy problems. We also research  how to use machine learning to help designers evaluate their systems design, as well as principled ways to design defenses against machine learning-based attacks on privacy.

Related publications:

Privacy evaluation

As systems become increasingly complex, they gather, and expose, increasing amounts of data . This information can be extracted from content, but also meta-data (timing patterns, locations, etc).

At the SPRING Lab we work on building tools to enable users to better understand how much information they reveal, and to enable app developers to achieve their goals without endangering the privacy of users that altruistically contribute to the projects.

Related publications: