Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 11
3338-3342

Classification method of mobile traffic based on image features

Zhang Lihua1a
Liu Bingnan2
Wang Junfeng1a,1b
1. a. School of Computer Science, b. School of Aeronautics & Astronautics, Sichuan University, Chengdu 610065, China
2. Information Engineering University, Zhengzhou 450001, China
DOI: 10.19734/j.issn.1001-3695.2019.07.0264

Abstract

The mobile traffic is increasing rapidly besides exists great risk in many operating systems because of the rapid development and application explosion of mobile devices. Therefore, it is of great significance to effectively distinguish mobile traffic and identify the operating system from huge network traffic for mobile malicious traffic analysis. Traffic analysis technology based on traditional features has the problem of relying too much on feature selection to classify mobile traffic steadily and effectively. Due to above reasons, this paper proposed a mobile traffic classification method based on image features, which visualized the traffic samples, transformed them into gray images and extracted the GLCM features of the images for classification. The experimental results show that the accuracy of the proposed method is 22.4% higher than that of the traditional method, which effectively solves the problems of feature selection and lack of good scalability of the traditional method. In addition, this paper studied the influence of traffic granularity(flow vs stream), classification granularity(two classifications vs multiple classifications) and the equilibrium of datasets(balance vs imbalance) on mobile traffic classification methods. The research shows that the influence degree of classification granularity has little effect on the proposed method, and the highest reduced accuracy is only 2.6%. The experimental results further illustrate the expansibility of this method, which can be effectively used in the security research field of subsequent mobile traffic.

Foundation Support

国家重点研发计划资助项目
国家自然科学基金资助项目
装备预研教育部联合基金资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.07.0264
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 11
Section: Algorithm Research & Explore
Pages: 3338-3342
Serial Number: 1001-3695(2020)11-028-3338-05

Publish History

[2020-11-05] Printed Article

Cite This Article

张丽华, 刘秉楠, 王俊峰. 一种基于图像特征的移动流量分类方法 [J]. 计算机应用研究, 2020, 37 (11): 3338-3342. (Zhang Lihua, Liu Bingnan, Wang Junfeng. Classification method of mobile traffic based on image features [J]. Application Research of Computers, 2020, 37 (11): 3338-3342. )

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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