Biblio

Information security construction is a social issue, and the most urgent task is to do an excellent job in information risk assessment. The bayesian neural network currently plays a vital role in enterprise information security risk assessment, which overcomes the subjective defects of traditional assessment results and operates efficiently. The risk quantification method based on fuzzy theory and Bayesian regularization BP neural network mainly uses fuzzy theory to process the original data and uses the processed data as the input value of the neural network, which can effectively reduce the ambiguity of language description. At the same time, special neural network training is carried out for the confusion that the neural network is easy to fall into the optimal local problem. Finally, the risk is verified and quantified through experimental simulation. This paper mainly discusses the problem of enterprise information security risk assessment based on a Bayesian neural network, hoping to provide strong technical support for enterprises and organizations to carry out risk rectification plans. Therefore, the above method provides a new information security risk assessment idea.

With the gradual construction and implementation of cloud computing, the information security problem of the smart grid has surfaced. Therefore, in the construction of the smart grid cloud computing platform, information security needs to be considered in planning, infrastructure, and management at the same time, and it is imminent to build an information network that is secure from terminal to the platform to data. This paper introduces the concept of cloud security technology and the latest development of cloud security technology and discusses the main strategies of cloud security construction in electric power enterprises.

Smart grids are envisioned as the next-generation electricity grids. The data measured from the smart grid is very sensitive. It is thus highly necessary to adopt data access control in smart grids to guarantee the security and privacy of the measured data. Due to its flexibility and scalability, attribute-based encryption (ABE) is widely utilized to realize data access control in smart grids. However, most existing ABE solutions impose a heavy decryption overhead on their users. To this end, we propose a lightweight attribute-based encryption scheme for data access control in smart grids by adopting the idea of computation outsourcing. Under our proposed scheme, users can outsource a large amount of computation to a server during the decryption phase while still guaranteeing the security and privacy of the data. Theoretical analysis and experimental evaluation demonstrate that our scheme outperforms the existing schemes by achieving a very low decryption cost.

A unified cloud management platform is the key to efficient and secure management of cloud computing resources. To improve the operation effect of the power cloud service platform, power companies can use the micro-service architecture technology to carry out data processing, information integration, and innovative functional architecture of the power cloud service platform, realize the optimal design of the power cloud service platform and improve the power cloud service platform-security service quality. According to the technical requirements of the power cloud security management platform, this paper designs the technical architecture of the power unified cloud security management platform and expounds on the functional characteristics of the cloud security management platform to verify the feasibility and effectiveness of the cloud security management platform.