NDLI: An application-level features mining algorithm based on PrefixSpan

Content Provider	IEEE Xplore Digital Library
Author	Guanzhou Lin Yang Xin Yixian Yang Yong Ji
Copyright Year	2010
Description	Author affiliation: Information Security Center, State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, China (Guanzhou Lin; Yang Xin; Yixian Yang) \|\| China Electronic Facility and System Engineering Company, Beijing, China (Yong Ji)
Abstract	Through matching the content of payload against common signatures found in the target application traffic, the approach based on application-level features is widely used in network traffic identification devices. Existing approaches to application feature identification involved a manual process which is time-consulting and complicated. In this paper, a novel application-level features mining algorithm based on PrefixSpan is proposed used to automatically extract features from network traffic. The algorithm mines the complete set of continuous patterns but greatly reduces the efforts of candidate subsequence generation. The experimental results show high precision and low error rate using these mined features in network traffic identification, and the algorithm outperforms the Apriori-based features mining algorithm.
File Size	195570
File Format	PDF
ISBN	9781424463473
e-ISBN	9781424463497
DOI	10.1109/ICCET.2010.5485474
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-04-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Protocols Error analysis Laboratories Application-level Feature Telecommunication traffic Telecommunication switching PrefixSpan Databases Information security Traffic control Systems engineering and theory Network Traffic Identification Sequential Pattern Mining Payloads
Content Type	Text
Resource Type	Article

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