Large

This project addresses how semiconductor designers can verify the correctness of ICs that they source from possibly untrusted fabricators. Existing solutions to this problem are either based on legal and contractual obligations, or use post-fabrication IC testing, both of which are unsatisfactory or unsound. As a sound alternative, this project designs and fabricates verifiable hardware: ICs that provide proofs of their correctness for every input-output computation they perform in the field.

Crypto-currencies and smart contracts are a new wave of disruptive technology that will shape the future of money and financial transactions. Today, crypto-currencies are a billion-dollar market, and hundreds of companies are entering this space, promising exciting new markets and eco-systems. Unfortunately, usage of crypto-currencies outstrips our understanding. Currently most crypto currencies rely on heuristic designs without a solid appreciation of the necessary security properties, or any formal basis upon which strong assurance of such properties might be achieved.

The potential benefits from electronic medical records (EMRs), including lab tests, images, diagnoses, prescriptions, and medical histories are without precedent. Patients and insurers can avoid repeating studies that, for example, expose people to additional radiation and incur unnecessary costs. Providers can instantly access patient histories , and patients can take ownership of their medical records, with the potential for greater privacy, and better access to their records when they are needed.

Data Protection laws that exempt data that is not individually identifiable have led to an explosion in anonymization research. Unfortunately, how well current de-identification and anonymization techniques control risks to privacy and confidentiality is not well understood. Neither is the usefulness of anonymized data for real-world applications. The project addresses anonymization on three fronts: 1) Textual data, even when explicit identifiers are removed (names, dates, locations), can contain highly identifiable information.

Data Protection laws that exempt data that is not individually identifiable have led to an explosion in anonymization research. Unfortunately, how well current de-identification and anonymization techniques control risks to privacy and confidentiality is not well understood. Neither is the usefulness of anonymized data for real-world applications. The project addresses anonymization on three fronts: 1) Textual data, even when explicit identifiers are removed (names, dates, locations), can contain highly identifiable information.