Confidential information protection method of commercial information physical system based on edge computing

Big data network security defense mode of deep learning algorithm

With the rapid development and progress of big data technology, people can already use big data to judge the transmission and distribution of network information and make better decisions in time, but it also faces major network threats such as Trojan horses and viruses. Traditional network security functions generally wait until the network power is turned on to a certain extent before starting, and it is difficult to ensure the security of big data networks. To protect the network security of big data and improve its ability to defend against attacks, this article introduces the deep learning algorithm into the research of big data network security defense mode. The test results show that the introduction of deep learning algorithms into the research of network security model can enhance the security defense capability of the network by 5.12%, proactively detect, and kill cyber attacks that can pose threats. At the same time, the security defense mode will evaluate the network security of big data and analyze potential network security risks in detail, which will prevent risks before they occur and effectively protect the network security in the context of big data.

Effect of Protein Nutrition Level on Protein Metabolism during Volleyball Exercise Based on Edge Computing in the Medical System

With the rapid development of the Internet of Things, 5G, and communication technologies, the growth of various types of data has shown an exponential trend. Edge computing technology provides users with almost unlimited computing power through a large number of high-performance servers in the data center. It is one of the important solutions for big data analysis and processing. Volleyball has caused a great wave in China as early as the 1960s, but people pay little attention to the physical quality of volleyball players. At the same time, in the medical field, it is difficult to give a clear value to the athlete's protein requirement. Therefore, this article aims to observe the specific values of protein metabolism in volleyball at different levels of protein nutrition. By designing controlled experiments, then these rats under three nutrient levels of protein were observed and protein metabolism was analyzed after volleyball. The results of the study show that volleyball exercise can reduce the nitrogen balance and gastrocnemius nitrogen content. The nitrogen balance of the 17% group decreased from 388 mg/day before exercise to 336 mg/day, and the gastrocnemius nitrogen content decreased by up to 5.2%; serum urea nitrogen concentration and liver nitrogen content are increased, indicating the enhancement of protein catabolism. Different protein nutrition levels have different effects on protein metabolism during volleyball. The protein intake level of 17% is more conducive to resist the protein decomposition caused by volleyball. It can be seen that, based on edge computing technology, the influence factors of protein nutrition level on protein metabolism during volleyball sports can be well explored, and the research results are also very valuable.