A novel method for network traffic classification based on robust support vector machine. Issue 11 (11th October 2020)

• Record Type: Journal Article
• Authors: Qu, Hua; Jiang, Jie; Zhao, Jihong; Zhang, Yanpeng; Yang, Jinli
• Is Part Of: Transactions on emerging telecommunications technologies. Volume 31:Issue 11(2020)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2020-10-11
• Subjects: Telecommunication -- Periodicals; 384.05
• DOI: 10.1002/ett.4092
• Languages: English
• ISSNs: 2161-5748

Abstract

ABSTRACT: The increasing demand for high‐speed transmission and traffic classification has been widely applied for network resource management, quality of service, dynamic access control, and others. Some normal machine learning algorithms for network traffic classification are becoming obsolete, as the increasing deployment of encryption in protocols and dynamic ports, as well as some new technology are available, such as HTML5 protocols and HTTP adaptive streaming in video traffic. This article presents a novel classification algorithm for video traffic. We produce a new video traffic dataset and propose an original parameter adaptive algorithm for robust support vector machine with a fuzzy membership function. The results show that the proposed model is an effective alternative to be applied in actual network environment. Abstract : This article presents a novel classification algorithm for video traffic. We produce a new video traffic dataset and propose an original parameter adaptive algorithm for robust support vector machine with a fuzzy membership function.