PRIVACY-SENSITIVE RANKING OF USER DATA

摘要

One embodiment of the present invention provides a system for privacy-sensitive ranking of aggregated data. During operation, the system distributes secret keys to a plurality of devices. The system then generates a plurality of probability density functions in a privacy-preserving way using encrypted data received from a subset of the plurality of devices. The encrypted data is data that has been encrypted with one or more of the secret keys by the subset of devices. The system then generates a plurality of probability mass functions, each probability mass function associated with a corresponding probability density function. Subsequently, the system computes a plurality of distance values, each respective distance value being a measure of distance from a probability mass function to a second distribution. The system then ranks the probability mass functions and/or associated attributes according to their respective distance from the second distribution.

主权项

1. A computer-executable method for privacy-sensitive ranking of aggregated data, comprising:
distributing secret keys to a plurality of devices; generating a plurality of probability density functions in a privacy-preserving way using encrypted data received from a subset of the plurality of devices, wherein the encrypted data is encrypted with one or more of the secret keys; generating a plurality of probability mass functions, each probability mass function associated with a corresponding probability density function; computing a plurality of distance values, each respective distance value being a measure of distance from a probability mass function to a second distribution; and ranking the probability mass functions and/or associated attributes according to their respective distance from the second distribution.