Network intrusion detection model based on multivariate correlation analysis - long short-time memory network
Dong, Rui-Hong; Li, Xue-Yong; Zhang, Qiu-Yu; Yuan, Hui
2020-03
Source PublicationIET INFORMATION SECURITY
ISSN1751-8709
Volume14Issue:2Pages:166-174
AbstractFor the purpose of improving the low detection performance of network intrusion detection model caused by high-dimensional data, and from the perspective of time correlation characteristics of intrusion detection datasets, the authors present a network intrusion detection model based on the multivariate correlations analysis - long short-term memory network (MCA-LSTM). Firstly, this model selects the optimal feature subsets through the information gain feature selection method, the MCA module is then used to change the feature subset into the triangle area map (TAM) matrix, and finally inputs the TAM matrix into the LSTM module for the training and testing purpose. To better demonstrate the performance of the proposed model, it is compared with those of convolutional neural networks, recurrent neural network, deep forest, support vector machine, and k-nearest neighbour methods proposed by the previous researchers. Experimental results show that the testing accuracy of the proposed model on 5-classification task using NSL-KDD dataset is up to 82.15%, and that on 10-classification task using UNSW-NB15 dataset is up to 77.74%. Moreover, compared with the traditional machine learning and existing deep learning models, the proposed model has shown to achieve better classification detection performance.
Keywordsupport vector machines neural nets image classification pattern classification security of data recurrent neural nets learning (artificial intelligence) network intrusion detection model multivariate correlation analysis short-time memory network low detection performance time correlation characteristics intrusion detection datasets multivariate correlations analysis short-term memory network information gain feature selection method convolutional neural networks recurrent neural network classification detection performance
DOI10.1049/iet-ifs.2019.0294
Indexed BySCI
Language英语
Funding ProjectNational Natural Science Foundation of China[61862041][61363078]
WOS Research AreaComputer Science
WOS SubjectComputer Science, Information Systems ; Computer Science, Theory & Methods
WOS IDWOS:000515534600003
PublisherINST ENGINEERING TECHNOLOGY-IET
Citation statistics
Cited Times [WOS]:0   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.lut.edu.cn/handle/2XXMBERH/56777
Collection计算机与通信学院
Corresponding AuthorZhang, Qiu-Yu
AffiliationLanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
First Author AffilicationLanzhou University of Technology
Corresponding Author AffilicationLanzhou University of Technology
First Signature AffilicationLanzhou University of Technology
Recommended Citation
GB/T 7714
Dong, Rui-Hong,Li, Xue-Yong,Zhang, Qiu-Yu,et al. Network intrusion detection model based on multivariate correlation analysis - long short-time memory network[J]. IET INFORMATION SECURITY,2020,14(2):166-174.
APA Dong, Rui-Hong,Li, Xue-Yong,Zhang, Qiu-Yu,&Yuan, Hui.(2020).Network intrusion detection model based on multivariate correlation analysis - long short-time memory network.IET INFORMATION SECURITY,14(2),166-174.
MLA Dong, Rui-Hong,et al."Network intrusion detection model based on multivariate correlation analysis - long short-time memory network".IET INFORMATION SECURITY 14.2(2020):166-174.
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