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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 12
3765-3769,3802

Police cloud security data fusion technology based on one-dimensional convolutional neural network and improved D-S theory of evidence

Li Wei1
He Ming1
Xu Bing1
Qian Fahua2
Li Chen1
1. Institute of Command & Control Engineering, Army Engineering University of PLA, Nanjing 210007, China
2. Information Department, Jiangsu Provincial Public Security Department, Nanjing 210007, China
DOI: 10.19734/j.issn.1001-3695.2022.04.0201

Abstract

In order to solve the problems about single source of evaluation information, large deviation of accuracy and insufficient extraction fusion of heterogeneous data, this paper proposed a multi-source heterogeneous network security data fusion framework which could expand the attack behaviors. Firstly, this paper established a security event analysis model based on attack mode to further simplify security data. Secondly, aiming at the problem of insufficient data feature extraction at decision level, it established a 1D-CNN model based on the attack behaviors to learn and reconstruct the features of police security data. Finally, in order to improve the classification ability in police cloud network security situation data, it modified the D-S evidence theory to fuse data combined with the credibility of multi-source security data. The experiment shows that the improved D-S theory of evidence module based on the 1D-CNN model further improves the alarm recognition rate of security events in police cloud. Compared with other related technologies, the model has better analytical ability and a great significance for security intrusion detection and vulnerability analysis in police cloud.

Foundation Support

江苏省重点研发计划资助项目
军内科研项目
军队重点课题

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.04.0201
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 12
Section: Technology of Information Security
Pages: 3765-3769,3802
Serial Number: 1001-3695(2022)12-038-3765-05

Publish History

[2022-07-06] Accepted Paper
[2022-12-05] Printed Article

Cite This Article

李伟, 何明, 徐兵, 等. 基于一维卷积神经网络与改进D-S证据理论的警务云安全数据融合技术 [J]. 计算机应用研究, 2022, 39 (12): 3765-3769,3802. (Li Wei, He Ming, Xu Bing, et al. Police cloud security data fusion technology based on one-dimensional convolutional neural network and improved D-S theory of evidence [J]. Application Research of Computers, 2022, 39 (12): 3765-3769,3802. )

About the Journal

  • 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.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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