Research On Data Privacy Protection And Secure Transmission Technology Based On Smart Meter System

Nowadays,there are more and more research and development achievements in the direction of intelligence in all walks of life.The great contribution of intelligence to society has made it an important engine for promoting social change and progress.Smart grid is an important direction in the research and development of power supply system.It is estimated that the global smart grid network market capacity will reach 89.4 billion U.S.dollars by 2025.As the core equipment of the smart grid,smart meters have attracted great attention of the whole society.Smart meters can collect users’ electricity consumption data and generate massive amounts of electricity consumption information.Through the analysis of these data,power companies can clearly understand the power consumption of each user and accurately predict the user’s approximate power consumption for a period of time in the future,so they can timely adjust the electricity price and power reserve and provide better and more accurate services for the whole society.However,these massive amounts of data contain sensitive information from all walks of life.If the sensitive information is not protected and is leaked,it will cause serious damage to the stable and healthy development of the whole society.So far,many researchers have proposed different privacy protection and secure transmission schemes for smart meter data.The core ideas of these schemes can be roughly divided into three categories: One is to hide sensitive information by modifying data;another is to ensure the secure transmission of data by means of encryption;the other is to realize the security of the electric meter by researching more reliable batteries.However,each scheme has many negative effects,such as excessive errors in modifying data,vulnerability in resisting attacking and tampering when using encryption methods,and the cost problem caused by improving the battery and so on.Most of the existing schemes do not give too much consideration of how to compromise the negative effects of various schemes.Based on the above issues,this thesis considers the advantages and disadvantages of each scheme,and combines the privacy protection of sensitive data with the secure transmission of the entire data.At the same time,considering the security,utility and computational efficiency of data,this thesis proposes two more advanced and efficient schemes to realize the privacy protection and secure transmission of big data in the power system.The first scheme is named Secure-Smart-Meter-System(SecSMS),and the second is named Privacy-Secure-Smart-Meter(PSSM).The details of the schemes are made as follows:(1)In order to improve the efficiency of privacy protection,reduce the error of modifying data,and increase the use space of aggregated data equipment,we adopt a technology that combines wavelet transform and Gaussian-Distributed Differential Privacy(GDDP)to protect data privacy;(2)The scheme of this thesis uses a scaling mechanism to balance the utility of data and the computational cost of data processing,and minimize the impact on data accuracy;(3)In order to ensure the integrity and secure transmission of the data,SecSMS uses Boneh-Lynn-Shacham(BLS)signature technology to verify the correctness of the data and ensure the unforgeability of the data;(4)On the basis of SecSMS scheme,PSSM improves BLS signature technology and adopts more advanced Schnorr signature technology to verify the correctness of smart meter data,and ensure the integrity and unforgeability of the data;(5)This thesis proposes a five-layer structure model framework to realize the secure and orderly transmission of data;(6)At the same time,this thesis also uses a data aggregation module that collects electricity consumption data of all users in a specific area,and then randomly sends each user’s data to the Data Processing Nodes(DPNs)for data processing.Since the smart meter is a device with limited hardware,the two schemes in this thesis use a lightweight privacy protection method to process user energy consumption data.The theoretical analysis and experimental results of this thesis show that the two schemes proposed in this thesis are superior to the existing schemes in terms of utility,security and computational efficiency.Compared with other existing schemes,the computational cost of the first scheme in this thesis is reduced by at least 6 times,and the computational cost of the second scheme is reduced by at least 8 times compared with the first scheme.The smart meter system is more practical to use the scheme proposed in this thesis.