Network threat situation assessment based on unsupervised multi-source data feature analysis

Aiming at the limitations of supervised neural network in the network threat testing task relying on data category tagging,a network threat situation evaluation method based on unsupervised multi-source data feature analysis was proposed.Firstly,a variant auto encoder-generative adversarial network...

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Main Authors: Hongyu YANG, Fengyan WANG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2020-02-01
Series:Tongxin xuebao
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Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020015/
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author Hongyu YANG
Fengyan WANG
author_facet Hongyu YANG
Fengyan WANG
author_sort Hongyu YANG
collection DOAJ
description Aiming at the limitations of supervised neural network in the network threat testing task relying on data category tagging,a network threat situation evaluation method based on unsupervised multi-source data feature analysis was proposed.Firstly,a variant auto encoder-generative adversarial network (V-G) for security threat assessment was designed.The training data set containing only normal network traffic was input to the network collection layer of V-G to perform the model training,and the reconstruction error of the network output of each layer was calculated.Then,the reconstruction error learning was performed by the three-layer variation automatic encoder of the output layer,and the training abnormal threshold was obtained.The packet threat was tested by using the test data set containing the abnormal network traffic,and the probability of occurrence of the threat of each group of tests was counted.Finally,the severity of the network security threat was determined according to the probability of threat occurrence,and the threat situation value was calculated according to the threat impact to obtain the network threat situation.The simulation results show that the proposed method has strong characterization ability for network threats,and can effectively and intuitively evaluate the overall situation of network threat.
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spelling doaj-art-9e5762982c79488183757f09f9d47c5a2025-01-14T07:18:36ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2020-02-014114315459733270Network threat situation assessment based on unsupervised multi-source data feature analysisHongyu YANGFengyan WANGAiming at the limitations of supervised neural network in the network threat testing task relying on data category tagging,a network threat situation evaluation method based on unsupervised multi-source data feature analysis was proposed.Firstly,a variant auto encoder-generative adversarial network (V-G) for security threat assessment was designed.The training data set containing only normal network traffic was input to the network collection layer of V-G to perform the model training,and the reconstruction error of the network output of each layer was calculated.Then,the reconstruction error learning was performed by the three-layer variation automatic encoder of the output layer,and the training abnormal threshold was obtained.The packet threat was tested by using the test data set containing the abnormal network traffic,and the probability of occurrence of the threat of each group of tests was counted.Finally,the severity of the network security threat was determined according to the probability of threat occurrence,and the threat situation value was calculated according to the threat impact to obtain the network threat situation.The simulation results show that the proposed method has strong characterization ability for network threats,and can effectively and intuitively evaluate the overall situation of network threat.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020015/unsupervisedmulti-source data feature analysisV-Gthreat probabilitythreat situation assessment
spellingShingle Hongyu YANG
Fengyan WANG
Network threat situation assessment based on unsupervised multi-source data feature analysis
Tongxin xuebao
unsupervised
multi-source data feature analysis
V-G
threat probability
threat situation assessment
title Network threat situation assessment based on unsupervised multi-source data feature analysis
title_full Network threat situation assessment based on unsupervised multi-source data feature analysis
title_fullStr Network threat situation assessment based on unsupervised multi-source data feature analysis
title_full_unstemmed Network threat situation assessment based on unsupervised multi-source data feature analysis
title_short Network threat situation assessment based on unsupervised multi-source data feature analysis
title_sort network threat situation assessment based on unsupervised multi source data feature analysis
topic unsupervised
multi-source data feature analysis
V-G
threat probability
threat situation assessment
url http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020015/
work_keys_str_mv AT hongyuyang networkthreatsituationassessmentbasedonunsupervisedmultisourcedatafeatureanalysis
AT fengyanwang networkthreatsituationassessmentbasedonunsupervisedmultisourcedatafeatureanalysis