Effective behavior signature extraction method using sequence pattern algorithm for traffic identification

Kyu‐Seok Shim, Sung‐Ho Yoon, Baraka D. Sija, Jun‐Sang Park, Kyunghee Cho and Myung‐Sup Kim

International Journal of Network Management, 2018, vol. 28, issue 2

Abstract: With the rapid development of the internet and a vigorous emergence of new applications, traffic identification has become a key issue. Although various methods have been proposed, there are still several limitations to achieving fine‐grained and application‐level identification. Therefore, we previously proposed a behavior signature model for extracting a unique traffic pattern of an application. Although this signature model achieves a good identification performance, it has trouble with the signature extraction, particularly from a huge amount of input traffic, because a Candidate‐Selection method is used for extracting the signature. To improve this inefficiency in the extraction process, in this paper, we propose a novel behavior signature extraction method using a sequence pattern algorithm. The proposed method can extract a signature regardless of the volume of input traffic because it excludes certain unsatisfactory candidates using a predefined support value during the early stage of the process. We proved experimentally the feasibility of the proposed extraction method for 7 popular applications.

Date: 2018
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Persistent link: https://EconPapers.repec.org/RePEc:wly:intnem:v:28:y:2018:i:2:n:e2011

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