This paper presents an accuracy-constrained privacy-preserving access control framework for relational data, which balances privacy protection against unauthorized access while maintaining the precision of information. The proposed system uses heuristics for anonymization algorithms to satisfy privacy requirements such as k-anonymity and l-diversity, while ensuring accuracy constraints for multiple roles. By integrating access control with privacy protection mechanisms, the framework aims to minimize imprecision in secured data queries.