Develop System Design Methods

Cloud computing poses significant risks to the security of client data. Virtual Machine Monitors (VMMs) that underlie cloud systems typically have all-powerful administrative domains that can be exploited or misused to snoop on client virtual machines (VMs) and steal/modify their data. Moreover, although virtual machine technology enables several novel security services that clients may wish to use, such services are privileged and must be implemented within the administrative domain.

Due to the ever-increasing complexity of both hardware and software, it is becoming harder to ensure the reliability of high-level programs. The project will develop tools that permit programmers to mechanically verify software via machine-code analysis. The proposed research will similarly advance the science of software analysis, together with the development of rigorous tools capable of performing industrial software verification. The tools are actively being used by industry for hardware specification and analysis.

Differential Privacy has emerged as a well-grounded approach to balancing personal privacy and societal as well as commercial use of data. The basic idea is to add random noise to analysis results sufficient to obscure the impact of any single individual's data on the analysis, thus protecting individual privacy. While general approaches to providing differential privacy exist, in many cases the bounds are not tight; more noise is added than needed. This project uses information theoretic techniques to explore the fundamental privacy/accuracy tradeoffs in differential privacy.

The objective of this project is to understand and strengthen the security of Multipath TCP (MPTCP) - an IETF standardized suite of TCP extensions that allow one MPTCP connection, consisting of multiple sub-connections between two hosts, to use multiple paths simultaneously. Even though MPTCP has been gaining momentum in being widely deployed, its security is yet to be well understood. The project is expected to raise awareness of MPTCP security and ultimately yield a foundation for MPTCP security.

Most cryptographic applications crucially rely on secret keys that are chosen randomly and are unknown to an attacker. Unfortunately, the process of deriving secret keys in practice is often difficult, error-prone and riddled with security vulnerabilities. Badly generated keys offer a prevalent source of attacks that render complex cryptographic applications completely insecure, despite their sophisticated design and rigorous mathematical analysis.