Research On Privacy Protection Of Data Aggregation And User Query In Smart Grid

In recent years,with the deepening of information technology applications,the development trend of smart grids as the next generation of power grids has pointed out the direction for the development of energy internet in the power industry.The smart grid will generate a large amount of valuable data,which is generated in real-time along with power production and consumption.The data has high real-time,authenticity,and privacy,and runs through all aspects of the power system’s"generation,transmission,distribution,and utilization".The goal of smart grid privacy protection research is to achieve the goal of data privacy without leakage while leveraging the potential value of these data.However,the existing smart grid privacy protection research still has problems such as low security,privacy leakage risk,low efficiency,single data utilization function and inability to resist quantum computer attacks in the process of data collection and sharing when balancing data availability and privacy.Especially in the research of smart grid data aggregation,there are problems such as single operational function,chaotic aggregation efficiency and process,and data privacy risks.The research of smart grid data query has problems such as low utilization of data value,single sharing function,risk of privacy leakage in query data,and low computational and communication efficiency.To address the above issues,this thesis proposes corresponding privacy protection and data sharing solutions for the five key scenarios of smart grid,in order to achieve privacy protection,anti-collusion,anti-quantum attacks,diverse data aggregation and query functions,efficient sharing,and low communication costs.The specific work of this thesis is as follows:(1)A lightweight data aggregation privacy protection and sharing solution based on dual blockchain is proposed to address the issues of single operation function,low data utilization efficiency,poor scalability of single blockchain,and privacy leakage risk in data aggregation research in smart grid.First,a lightweight distributed cloud storage architecture based on dual blockchain is proposed.This architecture stores encrypted data and returns addresses to protect data privacy.Utilize private blockchain to map associations between real identities and pseudonyms.At the same time,create a new shared blockchain for nodes with access control to reduce costs,ensure security,and reduce resource consumption.Then,a secure signature authentication and identity based proxy re-encryption strategy are designed.Here,encryption and signature schemes based on bilinear pairings are used to aggregate data to support low-cost and high-performance computing.Finally,the security and performance of the proposed scheme are evaluated.The evaluation results indicate that this scheme has the advantages of privacy protection,low latency,low response time,and low storage cost,and can meet the growing demand for full business data security communication in smart grid.(2)A multi-level certificateless aggregation signature and query scheme for privacy protection based on mobile fog computing is proposed to address the issues of low data collection and processing efficiency,chaotic collection process,poor mobility function,and privacy leakage risk in data aggregation research in smart grid mobile scenarios.Firstly,a multi-level dynamic privacy protection certificate less aggregation signcryption method without trusted permissions is proposed.In this scheme,data aggregation includes data aggregation based on space and time,and meets the aggregation needs of multiple functions of multivariate data.In order to improve the security of key management,a key pool is introduced here to quickly distribute keys.Secondly,based on certificateless signature encryption,a data query and sharing method based on proxy re-encryption is designed.This method not only supports users to query historical data and invoices,but also achieves secure data sharing with other third parties.Finally,the security of the proposed scheme is formally analyzed and digital simulation experiments are designed.The experimental results show that this scheme has the characteristics of high efficiency,lightweight,and robustness.(3)A privacy protection range query scheme based on inner product encryption and blockchain is proposed to address the issues of low utilization of data value,single and inflexible query functions,and the risk of data privacy leakage in a large number of decentralized device data systems in smart grid.Firstly,a smart grid architecture based on consortium blockchain is designed.This architecture allows authorized users or participants to enjoy high-quality data services with the help of the consortium blockchain nodes.Then,based on this architecture,a privacy protection range query scheme based on inner product encryption and consortium blockchain is proposed.This scheme combines the consortium blockchain and the inner product function encryption technology to realize the flexible,secure and batch query of data services in edge computing.This scheme utilizes data format conversion to reduce the magnitude of data,providing a foundation for efficient data querying.At the same time,it cleverly transforms the data range query problem into a mathematical inner product problem,providing the possibility for the implementation of inner product encryption.Finally,the safety and experimental performance of the proposed scheme are evaluated.Analysis shows that this scheme not only protects privacy but also effectively resists collusion query inference attacks,proving that the scheme is efficient,scalable,and flexible.(4)Aiming at the problems of data privacy leakage risk and low utilization efficiency,collusion risk caused by strong correlation between data and user identity in smart grid data query,a privacy protection range query scheme based on GM homomorphic encryption and blockchain is proposed.Firstly,a blockchain based universal three-layer architecture for smart grid is explored,including the edge layer,permissioned blockchain layer,and application layer.Secondly,based on the three-tier architecture,a novel query scheme for the privacy protection scope of smart grid is studied by applying fog computing,permissioned blockchain,Paillier homomorphic encryption system and GM homomorphic encryption system.Under the premise of protecting privacy and resisting collusion attacks,this scheme uses homomorphic encryption,fog computing and permissioned blockchain to realize batch range query in smart grid.This scheme utilizes the homomorphic XOR feature of GM and the confusion feature of bulletin boards to weaken the association between identity and data itself,achieving the goal of protecting privacy.The aggregation operation here also improves the efficiency of the solution.Security analysis shows that this scheme has the ability to protect privacy and resist collusion attacks.Finally,the security of the proposed scheme is analyzed and simulation experiments are designed.The analysis results indicate that the scheme has high efficiency and low storage capacity,and can meet the growing demand for data services.(5)Aiming at the problems that the data query system in smart grid cannot resist quantum attacks,repeated queries lead to resource waste,low query efficiency,and no cache mechanism,a dynamic range query privacy protection scheme based on lattice homomorphic encryption,blockchain and proxy re-encryption is proposed.First,a lattice-based homomorphic encryption algorithm is designed to resist quantum computer attacks,and data aggregation is implemented to improve efficiency.Then,a dynamic range query method using consortium blockchain and proxy re-encryption is proposed.This method avoids communication pressure caused by repeated data collection,improves query efficiency and user experience.Specifically,in order to improve data query efficiency,a three-level caching strategy is designed based on the caching principle.The first level is for data sets with high query frequency,the second level is for data sets with more queries for specific time periods,regions,or functional data sets,and the third level is for data sets with low query frequency that have appeared in previous query records.In addition,dynamic ciphertext and user updates are considered,further improving the flexibility and feasibility of the solution.Finally,the security of the proposed scheme is analyzed and simulation experiments are designed to analyze its performance.Security analysis and performance analysis indicate that the proposed solution meets the requirements of dynamic,privacy,security,and low computing costs.In summary,this thesis proposes corresponding privacy protection and data sharing solutions for five typical scenarios of smart grid data aggregation and user queries,in order to solve the problems of privacy leakage,low data utilization,potential collusion,inability to resist quantum attacks,low sharing efficiency,and high communication costs in smart grid data aggregation and user queries.