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...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Editorial Department of Journal on Communications
2020-02-01
|
| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2020015/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841539367980498944 |
|---|---|
| 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. |
| format | Article |
| id | doaj-art-9e5762982c79488183757f09f9d47c5a |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2020-02-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| 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 |