The researchers applied a ranking method to the routes to predict the top destinations for the trip. "We observed that in 60% of the cases, our algorithm placed the true destination in the top three possibilities," Dewri said. Even when the number of potential routes was large, the destinations often tended to end up with a small geographic area.
The study highlights the issue of unwanted disclosures, where consumers unknowingly reveal something they do not want to with data they are willing to reveal, Dewri said. "Unfortunately, there is no theory that will immediately tell what may get disclosed, or inferred, from the data we share."
The best way that consumers can protect themselves against privacy risks associated with usage-based insurance is to demand more transparency from their insurance companies, he noted.
"Programs using these devices should make the consumer aware of the potential risks, even if these programs are themselves not involved in making secondary inferences," Dewri said. "The clearer we are on how the data is used, the better methods we can design that will retain the utility of the data, without making it prone to unwanted inferences."
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