Research on Power Mobile Internet Security Situation Awareness Model Based on Zero Trust

Dai, Zaojian; Li, Nige; Li, Yong; Yuan, Guoquan; Zhao, Xinjian; Zhao, Ran; Wu, Fan

doi:10.1007/978-3-031-06791-4_40

Cited by 2 publications

(1 citation statement)

References 9 publications

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“…LSTM was used to predict data sets, and DT to identify attack types. e experiments proved that the situational awareness model proposed in this paper has a high accuracy.Dai et al [10] constructed a zero-trust method situational awareness model, which is a new theory emerging in recent years and has good application prospects.…”

Section: Introductionmentioning

confidence: 99%

A Situation Awareness Approach for Network Security Using the Fusion Model

Zhao

Zhang

2022

Mobile Information Systems

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Aiming at the limited learning ability of a single model, the objective of this paper is to investigate situational awareness of the network security which is established on the fusion model. In this paper, a convolutional neural network (CNN) and long short-term memory (LSTM)-based model for situational assessment of the network security condition are provided. According to different fusion methods, the parallel and serial CNN-LSTM fusion models were constructed to evaluate the UNSW-NB15 data set, and both the situation values and levels were obtained. The investigational outcomes illustrate that the evaluation accuracy of the two models can reach up to 85.19% and 92.59%, respectively. A situation prediction model called IPSO-ABiLSTM is suggested and is based on improved particle swarm optimization (IPSO) and attention fusion bidirectional long short-term memory (ABiLSTM). The IPSO has the characteristics of faster convergence speed to optimize the ABiLSTM network parameters and obtain the optimal parameters for situation prediction. The investigational outcomes illustrate that the suggested IPSO-ABiLSTM model has a fitting degree of up to 0.9922, which can effectively achieve the situation prediction in the network security.

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Section: Introductionmentioning

confidence: 99%