CORE

Recently, Google and Apple have deployed large systems for differentially private collection and analysis of decentralized user data. These systems use a local model of privacy in which no sensitive user data is collected. This local model enjoys many implementation advantages, but does not capture the most expressive private algorithms. These more expressive private algorithms inherently require a central model of privacy, in which a trusted party agrees to collect the sensitive data and reveal only the outcome of some private algorithm.

Software has bugs, quite commonly in libraries that are created by third-party developers. Unfortunately, a bug in any library enables attackers to take control of an application. Furthermore, since popular libraries are used across thousands of applications, these libraries become a high-leverage target for attackers. This work improves the security of software by stopping bugs in one library from impacting other portions of the application. This makes it much more difficult for attackers to compromise software and harm users.

Processing personal data in "the cloud" is an increasingly common computing application. For example, health monitors collect heartbeat data and upload to cloud for personal healthcare and wellbeing. This increases privacy and data security risks. This project aims to achieve provable security in the cloud by protecting data-access patterns in a security-oriented cloud architecture built on the recently released Intel SGX (Software Guard eXtensions) processor.

The proliferation of powerful smart-computing devices (e.g., smartphones, surveillance systems) capable of production, editing, analysis, and sharing of multimedia files and associated technological advances have affected almost every aspect of our lives. The use of digital multimedia (images, audio, and video) as evidence is rapidly growing in multiple applications, including legal proceedings and law enforcement.

Side-channel attacks have been proven effective to infer sensitive information (such as user activities) that should not be disclosed to unauthorized users. Owing to the closed nature of the cellular network infrastructure, adversaries cannot easily capture encrypted mobile network traffic, thus protecting against side-channel information leakage of mobile users.