A Data Masking Scheme for Sensitive Big Data Based on Format-Preserving Encryption
Baojiang Cui, Baihui Zhang, KaiYue Wang · 2017
Development of big data has brought us convenience and benefits, but the privacy issues have become increasingly prominent. In order to solve the problem of personal sensitive information leakage, this paper propose a data masking scheme based on format-preserving encryption for privacy information. The scheme can be used to encrypt credit card number, date, e-mail address and other data with tight format limit, and ensure the ciphertext is still in the original format constraints. In addition, this paper propose a solution for large scale of data masking. Experiments on Spark show that our data masking scheme based on format-preserving encryption can achieve the purpose of masking sensitive information while preserving the data format, and the parallel computing can get high efficiency.