Transition to Practice

The Wireless Philadelphia Network (WPN) is a metropolitan?area network (MAN) consisting of thousands of Tropos 5210 wireless mesh routers distributed across the entire city of Philadelphia and connected by a fiber backbone. This project is employing this network as a testbed to investigate three diverse security challenges facing any large-scale wireless network servicing a heterogeneous population.

Secure computation allows users to collaboratively compute any program on their private data, while ensuring that they learn nothing beyond the output of the computation. Existing protocols for secure computation primarily rely on a boolean-circuit representation for the program being evaluated, which can be highly inefficient. This project focuses on developing secure-computation protocols in the RAM model of computation. Particularly challenging here is the need to ensure that memory accesses are oblivious, and do not leak information about private data.

One of the most significant challenges in cybersecurity is that humans are involved in software engineering and inevitably make security mistakes in their implementation of specifications, leading to software vulnerabilities. A challenge to eliminating these mistakes is the relative lack of empirical evidence regarding what secure coding practices (e.g., secure defaults, validating client data, etc.), threat modeling, and educational solutions are effective in reducing the number of application-level vulnerabilities that software engineers produce.

Our world has become increasingly reliant on integrated circuits (ICs). Mobile phones are deeply enmeshed in our everyday lives, we drive cars equipped with hundreds of ICs, and have come to depend on the power grid and other cyber physical systems that are controlled by ICs. Not surprisingly, the issue of securing hardware has become increasingly vital. A reverse engineering adversary may, for example, be motivated by extracting intellectual property from a circuit, cloning a design for product piracy, or creating a targeted backdoor for stealing cryptographic keys.

Support for research on distributed data sets is challenged by stakeholder requirements limiting sharing. Researchers need early stage access to determine whether data sets are likely to contain the data they need. The Broker Leads project is developing privacy-enhancing technologies adapted to this discovery phase of data-driven research. Its approach is inspired by health information exchanges that are based on a broker system where data are held by healthcare providers and collected in distributed queries managed by the broker.