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Using data without actually seeing the data. That’s the fresh approach Mayank Varia takes with cryptography—and with data science.“I think of it as social science that masquerades as mathematical science,” says Varia, associate professor in the Faculty of Computing & Data Sciences and codirector of the Center for Reliable Information Systems & Cyber Security (RISCS). “We’re using tools and principles from math—but for the purposes of achieving socially desirable outcomes, especially in the digital world.”
In order to achieve those desirable outcomes, Varia and some colleagues have had to build off the idea of “secure multi-party computation,” which allows parties to share data to accomplish a goal, while not sharing more than they want to with one another because their data might reveal information they need to protect.
“The goal is the computing of data without seeing it,” Varia says. “So basically it’s about helping people to get data science done where they don’t fully trust each other to do data sharing and they don’t fully distrust each other,” he explains.
In other words, they have an interest in doing data science together, just warily. This approach to data science has helped the City of Boston and the Boston Women’s Workforce Council reduce the gender wage gap. By using a data aggregation algorithm, employers are able to share salary information—without revealing the actual salaries of their employees.
Varia and others have also used cryptography to help the Greater Boston Chamber of Commerce’s Pacesetters Program determine how often large companies subcontract work to minority-owned businesses. Another application has been used to link criminal records and identify repeat perpetrators of sexual assault.
There’ll be more world-improving applications in the future, all while Varia continues toward his original goal back when he first shifted from mathematics to data science.