A reduction of 3-Sat problem from optimal sanitization in association rule hiding

Large repositories of data contain sensitive information that must be protected against unauthorized access. The protection of the confidentiality of this information has been a long-term goal for the database security research community and for the government statistical agencies. Recent advances in data mining and machine learning algorithms have increased the disclosure risks that one may encounter when releasing data to outside parties. Association rule hiding is one of important privacy preserving data mining problems. This paper review current approaches addressing data mining and Security and that reduces 3-SAT problem from optimal sanitization in association rule hiding.