A study published in “IEEE Transactions on Big Data” revealed how researchers were able to identify individuals from anonymized data sets produced within a city, Fast Company reports. The researchers took two data sets from Singapore that only had the time and place of each data point. The group from the MIT Senseable City Lab used an algorithm to match the users whose data was seen in both sets. Over the course of 11 weeks, the algorithm was able to match data subjects with a 95 percent accuracy rate. MIT Future Urban Mobility Group Postdoctoral Researcher Daniel Kondor said while it is important to work with large sets of data, people should be aware of the potential of identification in order to know the risks of sharing mobile data.
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