Scientific Foundations

group_project

Visible to the public CAREER: Securing Critical Infrastructure with Autonomously Secure Storage

Embedded systems currently rely on local and often insecure state retention for process control and subsequent forensic analysis. As critical embedded control systems (e.g., smart grids, SCADA) generate increasing amounts of data and become ever more connected to other systems, secure retention and management of that data is required. Attacks such as Stuxnet show that SCADA and other systems comprising critical infrastructure are vulnerable to the compromise of controllers and sensing devices, as well as falsification of data to circumvent anomaly detection mechanisms.

group_project

Visible to the public TWC: Small: Algorithms for Number-Theoretic Problems Arising in Cryptography

This project studies several questions that have applications to cryptography. One goal is to develop classical cryptosystems that are secure against quantum computers. In particular, the project explores the security of some of the recently proposed lattice-based systems. Another goal is to make systems that are currently being used more efficient. The project aims to improve some of the algorithms for constructing curves that can be used in cryptosystems. This project will have implications for understanding which cryptosystems should be used now or in the future.

group_project

Visible to the public TWC SBE: Small: Towards an Economic Foundation of Privacy-Preserving Data Analytics: Incentive Mechanisms and Fundamental Limits

The commoditization of private data has been trending up, as big data analytics is playing a more critical role in advertising, scientific research, etc. It is becoming increasingly difficult to know how data may be used, or to retain control over data about oneself. One common practice of collecting private data is based on "informed consent", where data subjects (individuals) decide whether to report data or not, based upon who is collecting the data, what data is collected, and how the data will be used.

group_project

Visible to the public TWC: Small: Noisy Secrets as Alternatives to Passwords and PKI

In order to establish a secure communication channel, each communicating party needs some method to authenticate the other, lest it unwittingly establish a channel with the adversary instead. Current techniques for authentication often rely on passwords and/or the public-key infrastructure (PKI). Both of these methods have considerable drawbacks since passwords are frequently breached, and PKI relies on central authorities which have proven to be less than reliable. Thus there is a need to use other sources of information for the communicating parties to authenticate each other.

group_project

Visible to the public TWC: Small: Rigorous and Customizable Spatiotemporal Privacy for Location Based Applications

Rapid advances in location based applications are leading to increased concern about location privacy. Current mobile operating systems only provide users with rudimentary location access controls - either to block or allow location access - which are inadequate and inefficient in mitigating privacy threats. Most existing location obfuscation mechanisms are based on syntactic privacy models that do not consider mobility and are hence vulnerable to inference attacks.

group_project

Visible to the public CAREER: Tracking, Revealing and Detecting Crowdsourced Manipulation

The goal of this project is to create the algorithms, frameworks, and systems for defending the open web ecosystem from emerging threats. This project aims to (i) analyze malicious tasks and behaviors of crowdturfers; (ii) detect malicious tasks on crowdsourcing platforms by developing novel malicious task detectors; (iii) design and build a task blacklist; (iv) uncover the ecosystem of crowdturfers and detect crowdturfers; (v) combine crowdturfer detection approaches with other malicious participants detection approaches.

group_project

Visible to the public CAREER: Tracking, Revealing and Detecting Crowdsourced Manipulation

The goal of this project is to create the algorithms, frameworks, and systems for defending the open web ecosystem from emerging threats. This project aims to (i) analyze malicious tasks and behaviors of crowdturfers; (ii) detect malicious tasks on crowdsourcing platforms by developing novel malicious task detectors; (iii) design and build a task blacklist; (iv) uncover the ecosystem of crowdturfers and detect crowdturfers; (v) combine crowdturfer detection approaches with other malicious participants detection approaches.

group_project

Visible to the public STARSS: Small: Detection of Hardware Trojans Hidden in Unspecified Design Functionality

Concern about the security and reliability of our electronic systems and infrastructure is at an all-time high. Economic factors dictate that the design, manufacturing, testing, and deployment of silicon chips are spread across many companies and countries with different and often conflicting goals and interests. In modern complex digital designs, behaviors at a good fraction of observable output signals for many operational cycles are unspecified and vulnerable to malicious modifications, known as Hardware Trojans.

group_project

Visible to the public  TWC: Medium: Privacy Preserving Computation in Big Data Clouds

Privacy is critical to freedom of creativity and innovation. Assured privacy protection offers unprecedented opportunities for industry innovation, science and engineering discovery, as well as new life enhancing experiences and opportunities.

group_project

Visible to the public TWC: Large: Collaborative: Computing Over Distributed Sensitive Data

Information about individuals is collected by a variety of organizations including government agencies, banks, hospitals, research institutions, and private companies. In many cases, sharing this data among organizations can bring benefits in social, scientific, business, and security domains, as the collected information is of similar nature, of about similar populations. However, much of this collected data is sensitive as it contains personal information, or information that could damage an organization's reputation or competitiveness.