Data integrity attacks against the distributed real-time pricing in the smart grid

• Main Authors: Xinyu Yang, Xialei Zhang, Jie Lin, Wei Yu, Xinwen Fu, Wei Zhao
• Format: Conference Proceeding
• Language: English
• Subjects: Data integrity attacks; Distributed databases; Distributed real-time pricing; Power generation; Pricing; Real-time systems; Renewable energy sources; Smart grid; Smart grids; Smart meters; Vulnerabilities analysis
• ISSN: 2374-9628
• DOI: 10.1109/PCCC.2016.7820657

In this paper, we address the issue of designing an effective distributed real-time pricing scheme in the smart grid and investigating its security resilience when the data integrity attack is in place. Different from existing research efforts, in this paper we develop a distributed real-time pricing scheme, which can maximize the welfare of all participants and improve the resilience to system failures, as well as consider both renewable and traditional power resources. By leveraging the distributed approach, we leverage the gradient projection mechanism to solve the distributed real-time pricing problem in participants' smart meters to improve the resilience to system failures. We also investigate the vulnerabilities of the distributed real-time pricing scheme by considering one typical data integrity attack, which can inject false data into communication interfaces. Via a combination of both theoretical analysis and performance evaluation, we demonstrate that the proposed distributed scheme can effectively guide the participants to achieve individual welfare maximization. Our findings also show that data integrity attacks can disrupt the distributed real-time pricing, posing a damage to the welfare of participants.