Uber, in a show of commitment to protecting rider and driver privacy, released a tool developed together with security researchers at the University of California, Berkeley, for differential privacy. Differential privacy makes it possible to generate general statistical analysis without revealing information about particular individuals in data sets.
Making the original tool, Elastic Sensitivity, compatible with SQL queries, helps companies add protection layers in addition to technical and administrative controls when many different database engines are in use. This way, the noise, an abstract term for protection added to sensitive information about single users, can be better adjusted to, for example, the size of a city.
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