Medium

This interdisciplinary project studies the nature of the risks inherent in normal activity on the Internet, the perception of those risks, the judgment about trade-offs in behavior and the design of a personalized agent that can alert users to risky behavior and help to protect them. The key insight is that adequate security and privacy protection requires the concerted efforts of both the computer and the user.

Developments in public-key encryption (PKE) and identity-based encryption (IBE) have revolutionized the field of cryptography and secure communication in general. PKE allowed remote parties to establish secure channels in front of eavesdropping adversaries, and led to public-key directories storing parties' public-keys. The stronger primitive of IBE eliminated the need for a large public-key directory, though this comes at the cost of trusting a central private-key generation authority.

Differential privacy (DP) has been accepted as the de facto standard for data privacy in the research community and beyond. Both companies and government agencies are trying to deploy DP technologies. Broader deployments of DP technology, however, face challenges. This project aims to understand the needs of different stakeholders in data privacy, and to develop algorithms and software to enable broader deployment of private data sharing.

Differential privacy (DP) has been accepted as the de facto standard for data privacy in the research community and beyond. Both companies and government agencies are trying to deploy DP technologies. Broader deployments of DP technology, however, face challenges. This project aims to understand the needs of different stakeholders in data privacy, and to develop algorithms and software to enable broader deployment of private data sharing.

There has been a rapid escalation of targeted cyber-attacks, called Advanced Persistent Threats (APTs), on high-profile enterprises. These skilled attacks routinely bypass widely deployed protection mechanisms. Existing second-line cyber defenses (e.g., intrusion detection systems) are helpful, but they often generate a flood of information that overwhelms cyber analysts. Moreover, analysts lack the tools to piece together attack fragments spanning multiple applications and/or hosts.