Quantitative selection of secure access policies for edge computing side terminals
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Aidong Xu, Qianru Wang, Yixin Jiang, Runfa Liao, Yunan Zhang, Yi Chen, Hong Wen, Jinran Du
As a new computing model in the era of Internet of things, edge computing has the characteristics of distributed, “data first entry”, relatively limited computing and storage resources, which make it not only face the widespread network attacks in information systems, but also inevitably introduce some new security threats, which need to implement end-to-end protection. Therefore, this paper mainly studies the terminal access security in the edge computing system, and puts forward the terminal security access strategy selection scheme based on BP neural network, which can comprehensively evaluate the security risks and threats faced by the terminal and data, select the appropriate algorithm according to the actual needs of the system, and select the security access strategy of the terminal on the edge computing side through quantitative objective standards, so as to realize the edge computing side Maximum optimization of safety performance of edge computing system.
Edge computing security; terminal access; quantitative assessment; strategy selection