A Computationally Efficient Method for Increasing Confidentiality in Smart Electricity Networks

Abstract

Safeguarding the data collected by smart meters is essential because the disclosure of this information may threaten the privacy of the consumer. By obtaining them, hackers can find out the behavior of the person and use that information for malicious purposes. Therefore, the anonymity of such information can prevent the occurrence of risks. Given the paramount significance of user privacy and data integrity, this paper primarily investigates the confidentiality, integrity, and anonymity of messages. This paper aims to develop a platform for determining dynamic pricing to coordinate supply and demand, thereby maximizing the efficiency of facilities. In the previous research, the operation center was not authenticated for the customer in the first step, and they also had a heavy computational cost. But this paper has endeavored to develop an efficient and comprehensive privacy-preserving solution for the smart electricity network. Also, it has tried to cover all the required security objectives by dealing with authenticity, confidentiality, and irrefutability. The method of the research is that two entities mutually authenticate each other and reach a key agreement so that if the operation center wants to send a control command, it can send control commands directly to the meter with less time complexity. The power company sends control commands and requests to the smart meters until the analyzed and collected energy consumption data are transmitted. The data aggregator node gathers the data from the meters. The results showed that the proposed method reduced the computational complexity and communication overhead to a satisfactory level and is also resistant to various attacks.