Title

SigBox: Automatic Signature Generation Method for Fine-Grained Traffic Identification

DOI

10.6688/JISE.2017.33.2.15

Authors

KYU-SEOK SHIM;SUNG-HO YOON;SU-KANG LEE;MYUNG-SUP KIM

Key Words

traffic identification ; traffic classification ; automatic signature generation ; sequence pattern algorithm ; Apriori algorithm

PublicationName

Journal of Information Science and Engineering

Volume or Term/Year and Month of Publication

33卷2期(2017 / 03 / 01)

Page #

537 - 569

Content Language

英文

Chinese Abstract

The continual appearance of new applications and their frequent updates emphasize the need for automatic signature generation. Although several automatic methods have been proposed, there are still limitations to their adoption in a real network environment in terms of automation, robustness, and elaboration. To address this issue, we propose an automatic signature generation method, so called SigBox, for fine-grained traffic identification. Using a modified sequence pattern algorithm, this system extracts three types of signatures: content, packet, and flow signature. A flow signature, the final result of this system, consists of a series of packet signatures, and a packet signature consists of a series of content signatures. A content signature is defined as a distinguishable and unique substring of the packet payload. By using the modified sequence pattern algorithm, we can improve the system performance in terms of automation and robustness. In addition, the proposed method can generate an elaborated signature for fine-grained traffic identification by using flow-level features beyond those of the packet level. In order to verify the feasibility of our proposed system, we present the results of experiments based on ten popular applications according to three defined metrics: redundancy, coverage, and accuracy. In addition, we show the quality of the generated signatures as compared to those produced by existing methods.

Topic Category 基礎與應用科學 > 資訊科學
Times Cited
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