Biblio

With the vigorous development of the Internet and the widespread popularity of smart devices, the amount of data it generates has also increased exponentially, which has also promoted the generation and development of cloud computing and big data. Given cloud computing and big data technology, cloud storage has become a good solution for people to store and manage data at this stage. However, when cloud storage manages and regulates massive amounts of data, its security issues have become increasingly prominent. Aiming at a series of security problems caused by a malicious user's illegal operation of cloud storage and the loss of all data, this paper proposes a threshold signature scheme that is signed by a private key composed of multiple users. When this method performs key operations of cloud storage, multiple people are required to sign, which effectively prevents a small number of malicious users from violating data operations. At the same time, the threshold signature method in this paper uses a double update factor algorithm. Even if the attacker obtains the key information at this stage, he can not calculate the complete key information before and after the time period, thus having the two-way security and greatly improving the security of the data in the cloud storage.

With the rapid construction and popularization of smart grid, the security of data in smart grid has become the basis for the safe and stable operation of smart grid. This paper proposes a data security threat discovery model for smart grid. Based on the prediction data analysis method, combined with migration learning technology, it analyzes different data, uses data matching process to classify the losses, and accurately predicts the analysis results, finds the security risks in the data, and prevents the illegal acquisition of data. The reinforcement learning and training process of this method distinguish the effective authentication and illegal access to data.