Volume 14 Number 10 (Oct. 2019)
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JSW 2019 Vol.14(10): 449-456 ISSN: 1796-217X
doi: 10.17706/jsw.14.10.449-456

The Software Gene-Based Test Set Automatic Generation Framework for Antivirus Software

Liang Bai1,Yu Rao1, Shiwei Lu2*, Xu Liu2, Yiyi Hu2
1 CNCERT, Beijing, China
2 Shanghai Roar Panda Network Technology Co., Ltd.

Abstract— After studying the existing test set generation methods of antivirus software and sample analysis methods based on manual experience, the paper proposes asoftware gene-based test set automatic generation framework for antivirus software. Most of current test set automatic generation frameworks have problems of unstable performance, time-consuming, and the fact that its test setcannot well reflect the density distribution character of the original dataset. In this paper, some improvements are made to resolve above problems. Experiment results show that the framework can efficiently generate the test sample set with the volume nomore than one tenth of the original data set, meanwhile the distribution characteristics of the original dataset can be retained.

Index Terms— Automatic generation framework, clustering, malware, software gene.


Cite: Liang Bai, Yu Rao, Shiwei Lu, Xu Liu, Yiyi Hu, "The Software Gene-Based Test Set Automatic Generation Framework for Antivirus Software," Journal of Software vol. 14, no. 10, pp. 449-456, 2019.

General Information

ISSN: 1796-217X (Online)
Frequency:  Bimonthly (Since 2020)
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, Google Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsw@iap.org
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