An Adaptive Intelligent Fuzzy Logic Classifier for Data Security and Privacy in Large Databases

Abstract

Proper data protection facilities and services are very important in organizations. Data security and privacy issues needs to be considered and applied in organizations to provide a successful business operation. Large organizations have adapted the implementation and application of policies related to data security and privacy as one of their core and important activities. Data classification process allows financial organizations to organize their data according to their needs. However data classification is a laborious activity with significant data to evaluate and categorize. Data classification process is needed for organizations to identify and apply appropriate policy and security settings such as private access control and encryption requirements. In this paper a fuzzy logic based classification is used to classify data and suggests a method that can determine requirements for data security and privacy in organizations based on organizational needs and government policies imposed on data. A new method for data access authorization is also developed based on fuzzy logic, which will assist in preserving privacy and security of data. A Case study is considered to present the effectiveness of the proposed methods.