PRIVACY PRESERVATION FRAMEWORK FOR ADVANCED METERING INFRASTRUCTURE

Integrating data from multiple sources have enabled countless sharing of data by data owners such as individuals, organizations, and governments. The sharing of data needs control and management to ensure the sensitivity of data is protected. Numerous research have studied on the management of data in the deployment of advanced metering infrastructure (AMI) to ensure the smooth process in data integration. Though, misuse of information which is considered as privacy violation may occurred in the management and sharing of sensitive data. Hence, it is essential to build a framework and design appropriate algorithms to manage integrated data efficiently and to avoid privacy violation. The algorithm will consist of data classification and ranking mechanism to ensure data is managed effectively. This paper lays out a privacy preservation framework for the proposed system. Finally, we correspondingly propose future research directions in the conclusion.