IDG Contributor Network: Sleep and other patterns pinpoint individuals in datasets, study finds
A human’s “real-world movements” are so unique that people can be distinguished by their patterns, a new study conducted by Columbia University and Google finds. And that’s even if the datasets are anonymized.
Sleep cycles captured by fitness IoT products, commuting schedules stored by bots, the days of the week that one goes to work and other habits could all one day be used to discern one person from another, the study says.
What’s more, the computer scientists say all you need is one dataset to obtain results, for example, a few bank card transactions.
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