Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS
Network intrusion discovery aims to detect the network attacks and abnormal network intrusion efficiently, that is an important protection implement in the field of cyber security. However, the traditional network intrusion discovery method are difficult to extract high-order features (such as spati...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2021-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9513285/ |
| _version_ | 1818587098562691072 |
|---|---|
| author | Zhijie Fan Zhiwei Cao |
| author_facet | Zhijie Fan Zhiwei Cao |
| author_sort | Zhijie Fan |
| collection | DOAJ |
| description | Network intrusion discovery aims to detect the network attacks and abnormal network intrusion efficiently, that is an important protection implement in the field of cyber security. However, the traditional network intrusion discovery method are difficult to extract high-order features (such as spatial-temporal information) from network traffic data. In this paper, we proposed an improved method of network intrusion discovery based on convolutional long-short term memory network. This method implements the convolution operation in deep learning into the network structure of long-short term memory and improves the accuracy of network intrusion discovery. In the experimental section, we compared with other similar methods, the result shows that the proposed method has some advantages in the aspects of overall network intrusion discovery index, detection index of different types, and AUC evaluation index. In addition, we applied our method to the network intrusion discovery scenarios of video surveillance system (VSS). The result shows that the proposed method has advantages in accuracy, recall, precision, and other similar methods. |
| first_indexed | 2024-12-16T09:03:28Z |
| format | Article |
| id | doaj.art-715dee4f43154da295c861ede65d0f56 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T09:03:28Z |
| publishDate | 2021-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-715dee4f43154da295c861ede65d0f562022-12-21T22:37:07ZengIEEEIEEE Access2169-35362021-01-01912274412275310.1109/ACCESS.2021.31047189513285Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSSZhijie Fan0https://orcid.org/0000-0003-3578-7889Zhiwei Cao1https://orcid.org/0000-0003-3107-7580School of Computer Science, Fudan University, Shanghai, ChinaInformation Security Technology Division, Third Research Institute of Ministry of Public Security, Shanghai, ChinaNetwork intrusion discovery aims to detect the network attacks and abnormal network intrusion efficiently, that is an important protection implement in the field of cyber security. However, the traditional network intrusion discovery method are difficult to extract high-order features (such as spatial-temporal information) from network traffic data. In this paper, we proposed an improved method of network intrusion discovery based on convolutional long-short term memory network. This method implements the convolution operation in deep learning into the network structure of long-short term memory and improves the accuracy of network intrusion discovery. In the experimental section, we compared with other similar methods, the result shows that the proposed method has some advantages in the aspects of overall network intrusion discovery index, detection index of different types, and AUC evaluation index. In addition, we applied our method to the network intrusion discovery scenarios of video surveillance system (VSS). The result shows that the proposed method has advantages in accuracy, recall, precision, and other similar methods.https://ieeexplore.ieee.org/document/9513285/Network securitynetwork intrusion discovery methoddeep learningconvolutional long-short term memory network |
| spellingShingle | Zhijie Fan Zhiwei Cao Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS IEEE Access Network security network intrusion discovery method deep learning convolutional long-short term memory network |
| title | Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS |
| title_full | Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS |
| title_fullStr | Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS |
| title_full_unstemmed | Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS |
| title_short | Method of Network Intrusion Discovery Based on Convolutional Long-Short Term Memory Network and Implementation in VSS |
| title_sort | method of network intrusion discovery based on convolutional long short term memory network and implementation in vss |
| topic | Network security network intrusion discovery method deep learning convolutional long-short term memory network |
| url | https://ieeexplore.ieee.org/document/9513285/ |
| work_keys_str_mv | AT zhijiefan methodofnetworkintrusiondiscoverybasedonconvolutionallongshorttermmemorynetworkandimplementationinvss AT zhiweicao methodofnetworkintrusiondiscoverybasedonconvolutionallongshorttermmemorynetworkandimplementationinvss |