Research On Privacy Protection Based On Fog Computing In Smart Grid

As one of the typical application scenarios of smart cities,smart grid significantly improve the reliability,flexibility,efficiency and load balancing of power systems by integrating various modern emerging technologies.With the rapid development of smart grid,more and more devices are connected to smart grid systems,resulting in massive data that brings a heavy computing and communication burden to systems which only relies on cloud computing to provide services.As a supplement to cloud computing,fog computing extends computing power to the network edge,and has features such as low latency and location awareness compared with cloud computing.Introducing fog computing into smart grid is an effective way to relieve system pressure,reduce latency,and improve service quality.While the smart grid based on fog computing is promising,the security and privacy challenges it faces cannot be underestimated.The electricity consumption data in the smart grid system normally contains users’ private information,which may cause great harm to the users if revealed.Furthermore,if the data is subject to attacks such as tampering and forgery during transmission,it may pose threats to the stability of the smart grid.Hence,it is of great practical importance to enhance the privacy protection of electricity consumption data in smart grid.In response to the weaknesses of existing smart grid schemes,the main work of this research is as follows:1.Considering the existing smart grid privacy protection schemes,few schemes realize the dynamic billing function based on real-time price while protecting data privacy.In this paper,we construct a data aggregation scheme based on fog computing that supports privacy protection and dynamic billing.Specifically,we design a four-tier architecture data aggregation framework using fog nodes to collect and aggregate electricity consumption data encrypted under the El Gamal cryptosystem,and employing distributed decryption to implement data statistics and bills generation based on real-time prices.In addition,we introduce a trusted third party to arbitrate disputed bills.Detailed security analysis demonstrates that the proposed scheme can guarantee data confidentiality,source authentication,and integrity.Compared with related schemes,experimental results show that the proposed scheme has lower computation overhead and communication overhead.2.Most existing smart grid privacy protection schemes rely on secure channels for key distribution,and rarely consider collusive attacks against entities within the system.However,such a security assumption is too high,and once attackers eavesdrop on the key,they can forge the user’s signature and obtain the user’s private information;moreover,if the entities within the system collude,the possibility of leaking the private information of a single user is extremely high.To address the above issues,we construct a data aggregation privacy protection scheme based on the Paillier cryptosystem.By constructing a partial key to ensure that attackers cannot forge a valid signature based on the eavesdropped key;and by adding random numbers to the electricity consumption data to resist collusion attacks by internal entities.In addition,the proposed scheme implements fault tolerance,which allows the electricity service provider to decrypt the correct values even if some smart meters fail during data transmission.The security analysis shows that the proposed scheme satisfies the security requirements,and the experimental results show that the proposed scheme has well performance.