Security Enhancement Algorithm of SM-254 Cloud System and Automated Personnel Identification of the Management in the Supply Chain Enterprise

Abstract

To resolve the problems pertinent to data loss and privacy leakage caused by hackers in the cloud system during the computational process, the symmetric encryption (SM)-254 algorithm is employed to optimize the security function based on the original algorithm of the cloud system. The personnel data of the supply chain enterprise are loaded through the backpropagation neural network (BPNN) algorithm, and an automated management model of the cloud system is constructed according to the management system and the personnel organization structure of each department. Thus, the automated identification system of the personnel management of the supply chain enterprise is realized. Through the establishment of an automated management system by the cloud system, the accuracy of a cloud system to capture data pertinent to the personnel management of supply chain enterprises has increased by about 90% and the accuracies of both text recognition and image recognition for personnel management systems of supply chain enterprises reach about 92%. Hence, it enables supply chain enterprises to save time, money, and personnel and increases flexibility and brings convenience to personnel management, which is conducive to the personnel training, evaluation, and subsequent development of enterprises. Consequently, automated management gives enterprises an upper hand to use talents flexibly and comprehensively and establish an intact database of human resources (HR). It is found that the security enhancement algorithm of the cloud system can greatly reduce the risk of information leakage in the HR database and greatly improve the operational efficiency of the supply chain enterprise.