Inference detection in statistical database using frequent pattern
K. N. Aravind, Amrit Anand, Greeshma Sarath · 2017
Statistical database (SDB) is widely used in commer-cial, business and multifarious domains of the like. Protecting the sensitive information in database is a critical issue with the rapid increase in usage of DBaaS (Data base as a service). Statistical database (SDB) contains sensitive information, so queries revealing data specific to a particular individual or event is not permitted. It only allows a user to perform aggregate statistical queries. At times, when a user executes a series of aggregate queries which helps the user draw enough statistics about a single individual, revealing the sensitive information. The main objective is to restrain the usage of the SDB such that only aggregate values are obtained. This paper proposes an algorithm to solve this issue using Frequent Pattern Mining technique. The proposed algorithm is validated and compared with the existing approaches.