Software Technology Research
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2454-2457,2468

Gated memory network approach for Web attack detection

Wang Jiabao
Xu Weiguang
Zhou Zhenji
Li Yang
Miao Zhuang
Army Engineering University of PLA, Nanjing 210007, China

Abstract

To solve the problem of large-scale network attack detection, this paper proposed a gated memory network method based on word vector feature representation and recurrent neural network. Firstly, this method transformed the network request data into low-dimension real-value vector sequence representation. And then, it extracted the features of request data by using the memory ability of gated recurrent neural network. Finally, it adopted the logistic regression classifier to achieve automatic detection of network attack. On the CSIC2010 public data set, this proposed method achieves 98.5% 10-fold cross-validation F1-score. Comparing with traditional methods, it can effectively improve the precision and recall rates for detecting network attack. The proposed method can detect network attacks automatically and has good detection results.

Foundation Support

国家重点研发计划基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.01.0169
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 8
Section: Software Technology Research
Pages: 2454-2457,2468
Serial Number: 1001-3695(2019)08-045-2454-04

Publish History

[2019-08-05] Printed Article

Cite This Article

王家宝, 徐伟光, 周振吉, 等. 网络攻击检测的门控记忆网络方法 [J]. 计算机应用研究, 2019, 36 (8): 2454-2457,2468. (Wang Jiabao, Xu Weiguang, Zhou Zhenji, et al. Gated memory network approach for Web attack detection [J]. Application Research of Computers, 2019, 36 (8): 2454-2457,2468. )

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  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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