Method And Apparatus For Privacy-Preserving Data Mapping Under A Privacy-Accuracy Trade-Off

摘要

A method for generating a privacy-preserving mapping commences by characterizing an input data set Y with respect to a set of hidden features S. Thereafter, the privacy threat is modeled to create a threat model, which is a minimization of an inference cost gain on the hidden features S. The minimization is then constrained by adding utility constraints to introduce a privacy/accuracy trade-off. The threat model is represented with a metric related to a self-information cost function. Lastly, the metric is optimized to obtain an optimal mapping, in order to provide a mapped output U, which is privacy-preserving.

主权项

1. A method of generating a privacy-preserving mapping of an input data set which is subject to a privacy threat, said method performed by a processor and comprising:
determining a relationship between said input data set Y and a set of hidden features S, wherein said relationship is not a deterministic function; minimizing a metric on the hidden features S subject to utility constraints in order to obtain an optimal mapping, wherein said metric describes the privacy threat and is based on a self-information cost function and said utility constraints are based on a distortion between the input data set and an output of said privacy-preserving mapping; and obtaining an output U of said optimal mapping, wherein said output is privacy-preserving on the hidden features.