Enhanced Security for Two Party Confidential Data

Data mining is the process of extracting hidden predictive information from large databases to support decision making process. There may be a chance of revealing sensitive information stored in dataware house during extraction of hidden details. To protect this consequence a method is proposed to securely integrate person-speci?c sensitive data from two data providers, whereby the integrated data still retains the essential information for supporting data mining tasks. Most real-life scenarios are in need for simultaneous data sharing and privacy preservation of person sensitive data. Enhanced security for two party confidential data adopts differential privacy, provides a rigorous privacy model and makes no assumption about an adversary’s background knowledge.