VPN construction method for multiple firewall environment

Kayashima, Makoto; Terada, Masato; Fujiyama, Tatsuya; Koizumi, Masatoshi; Katou, Eri

doi:10.1002/1520-684x(200012)31:14<57::aid-scj7>3.3.co;2-d

Cited by 1 publication

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“…As the network develops rapidly [1], people's living standards have gradually improved [2], and the growing scale of the network and the more and more complex network environment has led to a higher frequency of security problems, which greatly challenges the integrity and confidentiality of network data [3]. Although there are many security measures, such as firewalls [4] and anomaly detection [5], none of them can provide a systematic and holistic perception of the network, discover the problems and solve them, which leads to the emergence of Network Security Situational Awareness (NSSA) [6]. NSSA can fuse all available information to assess the situation of the network, provide network administrators with relevant decision bases, and minimize possible risks and losses, which is important for improving the monitoring capability and responsiveness of the network.…”

Section: Introductionmentioning

confidence: 99%

Network security situational level prediction based on a double-feedback Elman model

Jie

2022

IJCAI

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Network Security Situational Awareness (NSSA) is an important element in network security research.Predicting network security situational level can help grasp the network security situation. This study mainly focuses on the double-feedback Elman model. Firstly, NSSA was briefly introduced. Then, relevant indicators were selected to establish a security situational indicator system. A back-propagation neural network (BPNN) model was designed to evaluate the situational value. A dual-feedback Elman model was used to predict the future situational level. The actual network environment was built to conduct experiments. The results showed that the evaluation results of only three samples obtained by the BPNN model did not match the actual situation, with an accuracy of 90%, and the prediction results of only four samples obtained by the dual-feedback Elman model did not match the actual situation, with an accuracy of 96.67%. The experimental results verify the reliability of the network security situational level prediction method designed in this study. The NSSA method can be promoted and applied in practice. Povzetek: S pomočjo globokih nevronskih mrež so razvili metodo za napovedovanje glede varnosti v omrežjih.

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Section: Introductionmentioning

confidence: 99%

Network security situational level prediction based on a double-feedback Elman model

Jie

2022

IJCAI

View full text Add to dashboard Cite

show abstract

VPN construction method for multiple firewall environment

Cited by 1 publication

References 0 publications

Network security situational level prediction based on a double-feedback Elman model

Network security situational level prediction based on a double-feedback Elman model

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