Data privacy issues are gradually more becoming important for many applications. Usually, database in the area of data safety can be mostly classified into access control research and data confidentiality research. There is little overlie among these two areas. Access Control Mechanisms (ACM) safe the sensitive information from unauthorized users. Even sanctioned users may misuse the data to reveal the privacy of individuals to whom the data. The privacy safety mechanism provides a greater confidentiality for sensitive information to be shared. It is achieved by anonymization techniques [8]. Privacy is achieved by the high accuracy and consistency of the user information, i.e., the precision of user information. In this paper, it offers confidentiality (privacy) preserving access manage mechanism for Incremental relational data. It uses the accuracy forced privacy protected access control mechanism for incremental relational database framework here. It uses the concept of imprecision bound related to access control mechanism for preserving privacy. The imprecision bound is set for all queries. For the privacy protection mechanism, it uses the combination of both the k-anonymity and fragmentation method.