The Research On Privacy-preserving Data Aggregation Scheme In Smart Grid

Smart grid is a new type of grid that combines traditional grid with modern information technology,which enhances the compatibility,controllability and self-healing of the whole grid system;data aggregation technology enables smart grid to collect,process and transmit data more efficiently.However,the booming development of smart grid still has some problems and challenges in privacy-preserving data aggregation.In the process of data aggregation,it faces the security threat of users’ privacy information leakage,which affects the security and stability of smart grid system.In addition,smart grid has an increasing demand for fine-grained data analysis and efficiency.Therefore,how to design a data aggregation scheme that is secure,efficient and supports fine-grained data analysis becomes the focus of this thesis.Aiming at the problems existing in fine-grained analysis and privacy-preserving of data aggregation,this thesis firstly proposes a privacy-preserving multi-dimensional and multisubset data aggregation scheme.In this scheme,the Chinese residual theorem,Paillier encryption algorithm and super-increasing sequence are used to achieve multi-dimensional and multi-subset data aggregation to meet the needs of fine-granularity analysis of multidimensional power consumption data in smart grid.Secondly,in order to resist differential attack in multi-dimensional and multi-subset data aggregation,this thesis extends the original scheme and combines the differential privacy technology to provide differential privacy protection for fine-grained electricity data,which solves the problem that the current multidimensional data aggregation does not consider differential attack.In addition,this thesis proposes an additive privacy-preserving multi-subset data aggregation scheme,which generates different pseudonyms for users’ real identities based on elliptic curve cryptography and hash chain to protect users’ identity information.The Chinese residual theorem,Paillier encryption algorithm and super-increasing sequence are used to analyze the mean value,variance and oneway variance of multi-subset aggregated data,which solves the problem that multi-subset data aggregation is limited by simple aggregation function at present and meets the demand of smart grid for fine-granularity analysis of multi-subset aggregated data.Moreover,this scheme improves the flexibility of data aggregation through dynamic pricing and charging of electricity consumption,and has a good application prospect.Finally,through security proof,analysis and experimental comparison,the scheme proposed in this thesis performs well in computing overhead and communication overhead,and can provide certain data security.