Personal data anonymization with model verification

Abstract

Anonymization is the process to remove personal information from the data. Once the data is anonymized, the data may be used for creating machine-learning models without the risk of invading anyone's privacy. One of the keys to data anonymization is to make sure that the data is really anonymized so nobody could use the anonymized data to obtain private information. Different techniques for data anonymization are presented. Further, the data anonymization techniques are tested for true anonymization by comparing the results from these techniques to a random method of guessing. If the difference in the results is below a predetermined threshold margin, the data anonymization techniques are safe and ready for use.

CPC Classifications