SYSTEM FOR PRIVACY-PRESERVING MONETIZATION OF BIG DATA AND METHOD FOR USING THE SAME

摘要

The current invention provides a system and method for Data Owners to share with Data Seekers extracted insights from the Big Data, instead of raw data or anonymized raw data, thus reducing or eliminating privacy concerns on the data owned by the Data Owners. An Oblivious Pseudo Random Function (OPRF) is used, with operations using OPRFs occur over encrypted data, thus Data Owners learn only the primary object from Data Seeker and nothing else about the remainder of Data Owners' data. Similarly, Data Seeker learns a list of associated secondary objects and nothing else about Data Owners' data. The extent of sharing can be limited using a predefined threshold depending how much private information Data Owner is willing to share or Data Seeker is willing to pay.