BSF

Blockchains provide compelling security properties that enable powerful systems to be constructed without reliance on trusted third parties. Their rise has created successful, multi-billion dollar systems and has had a transformative impact on venture funding and the financial industry. Blockchains as currently designed, though, fail to enforce fairness for their users, meaning equal opportunities for fast transaction processing. The project investigators will seek to address the pervasive fairness deficiencies in blockchain systems.

By collecting sensor data from individuals in a user community, e.g., using their smartphones, it is possible to learn the behavior of communities, for example locations, activities, and events. Similarly, using data from personal health monitoring sensors, it is possible to learn about the health risks and responses to treatments for population groups. But is it possible to use the valuable information for the greater good without disclosing information about the individuals contributing the data? What about protecting this information from improper access?

Symmetric-key primitives are the lifeblood of practical cryptography, and are critical components of nearly any computer security system. The cryptographic community has developed a rich body of work on theoretically sound symmetric objects, but they are many orders of magnitude too slow for realistic usage. Thus, practitioners use fast primitives that have been designed to withstand known attacks, but which lack rigorous security guarantees based on natural mathematical problems.

Over the past decade, people have realized that failure to account for human factors has resulted in many software security problems. Yet, when software does feature user-centric design, it takes into account average user behavior rather than catering to the individual. Thus, systems designers have gone from designing for security experts to now appealing to the least common denominator.