Paper Info
Title
Effective Behavior Signature Extraction Method Using Sequence Pattern Algorithm For Traffic Identification
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.
Year
DOI
Venue
2018
10.1002/nem.2011
INTERNATIONAL JOURNAL OF NETWORK MANAGEMENT
Field
DocType
Volume
Data mining,Traffic identification,Airfield traffic pattern,Computer science,Algorithm,Inefficiency,Sequence pattern,The Internet
Journal
28
Issue
ISSN
Citations 
2
1055-7148
0
PageRank 
References 
Authors
0.34
10
6
Name
Order
Citations
PageRank
Kyu-Seok Shim177.72
sungho yoon241.76
Baraka D. Sija362.58
Jun-Sang Park4488.28
Kyunghee Cho560.89
Myung-Sup Kim632545.01