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Technology of Information Security
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3119-3123

Network traffic anomaly detection based on iForest and LOF

Hang Feilu1
Guo Wei1
Chen Hexiong1
Zhang Zhenhong1
Yi Dongyang2
1. Information Center, Yunnan Power Grid Co. , Ltd. , Kunming 650034, China
2. Network & Data Security Key Laboratory of Sichuan Province, University of Electronic Science & Technology of China, Chengdu 610054, China

Abstract

Network traffic anomaly detection is an important tool of anomaly detection system. The purpose of network traffic anomaly detection is to find the data different from most data in the traffic log, and treat these outliers as exceptions. The existing isolation forest(iForest) method based on tree separation has a defect: which cannot detect local anomalies. In order to overcome the defect, this paper proposed an unsupervised traffic anomaly detection method based on iForest and LOF nearest neighbor integration. Firstly, it improved the original iForest and LOF algorithms to enhance the detection accuracy and control the algorithm time. Then, it used the two improved algorithms to detect, and fused the results of two algorithms to get the final detection result. Finally, this paper validated this method on the self-made dataset. Experimental results show that the proposed method can effectively isolate anomalies, and obtain good traffic anomaly detection effect.

Foundation Support

国家自然科学基金资助项目(62072074,62076054,62027827,61902054,62002047)
国家重点研发计划前沿科技创新专项资助项目(2019QY1405)
四川省科技创新基地(平台)和人才计划资助项目(2020JDJQ0020)
四川省科技支撑计划资助项目(2020YFSY0010)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.03.0121
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 10
Section: Technology of Information Security
Pages: 3119-3123
Serial Number: 1001-3695(2022)10-037-3119-05

Publish History

[2022-05-24] Accepted Paper
[2022-10-05] Printed Article

Cite This Article

杭菲璐, 郭威, 陈何雄, 等. 基于iForest和LOF的流量异常检测 [J]. 计算机应用研究, 2022, 39 (10): 3119-3123. (Hang Feilu, Guo Wei, Chen Hexiong, et al. Network traffic anomaly detection based on iForest and LOF [J]. Application Research of Computers, 2022, 39 (10): 3119-3123. )

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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