Effective behavior signature extraction method using sequence pattern algorithm for traffic identification
- Authors
- Shim, Kyu-Seok; Yoon, Sung-Ho; Sija, Baraka D.; Park, Jun-Sang; Cho, Kyunghee; Kim, Myung-Sup
- Issue Date
- 3월-2018
- Publisher
- WILEY
- Citation
- INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT, v.28, no.2
- Indexed
- SCIE
SCOPUS
- Journal Title
- INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
- Volume
- 28
- Number
- 2
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/76856
- DOI
- 10.1002/nem.2011
- ISSN
- 1055-7148
- 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.
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