Computing Statistics from Private Data

In several domains, privacy presents a significant obstacle to scientific and analytic research, and limits the economic, social, health and scholastic benefits that could be derived from such research. These concerns stem from the need for privacy about personally identifiable information (PII), commercial intellectual property, and other types of information. For example, businesses, researchers, and policymakers may benefit by analyzing aggregate information about markets, but individual companies may not be willing to reveal information about risks, strategies, and weaknesses that could be exploited by competitors. Extracting valuable utility from the new "big data" economy demands new privacy technologies to overcome barriers that impede sensitive data from being aggregated and analyzed.