Technology Review: mining cellphone data without violating privacy
Technology Review recently highlighted research by Margaret Martonosi and colleagues from AT&T, Rutgers University, and Loyola University who have devised a way to mine cellphone data without revealing callers’ identity.
The researchers are working with billions of location data points from AT&T mobile phone calls and text messages made in Los Angeles and New York City. The team is creating a “mobility model” of the two cities that “aggregates the data, produces representative ‘synthetic call records’—then mathematically obscures any data that could tend to identify people,” Technology Review reports.
“Noise is injected into the model at points in order to reduce the likelihood of individuals being identifiable,” says Martonosi, who is the Hugh Trumbull Adams ’35 Professor of Computer Science at Princeton.
In other news, a research paper coauthored by Martonosi and Sharad Malik, George Van Ness Lothrop Professor of Engineering, has been identified as one of the 25 most significant papers from the first 20 years of the International IEEE Symposium on Field-Programmable Custom Computing Machines.
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EQN is a blog from Princeton University’s School of Engineering and Applied Science that highlights faculty, students and alumni who, through innovation and leadership, are changing the world.
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