Some approach to data masking as means to counteract the inference threat - Yesin, V.I.; Vilihura, V.V. (Radiotekhnika, 2019)
The goal of the article is to reveal the essence of some approach to data masking stored in the database as a means to counteract the inference threat. This approach is based on the principles of random permutation of the elements of a data field of the row column of the production database table data and dynamic masking. A distinctive feature of the proposed solution is the approach to the process of data shuffling, namely, shuffling data value elements within the demanded row field. It is possible to mask both an entire value of the field of the table row column and its part using this solution. The proposed approach differs from most of the typical commercial tools for masking sensitive data in that a preliminary physical change of sensitive data is made in the production database, and a user who has the appropriate rights can cancel these changes if it is necessary. The legitimate user in the proposed approach gets access to sensitive data due to the ability to transform (rewrite) the query “on the fly”, and the attacker can only read the previously modified data that is stored in the database. The proposed approach to data masking can be used in both production and non-production databases, expanding the possibilities of so-called static data masking.