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General Information
    • ISSN: 1793-8244
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Dr. Ka Wai Gary Wong
    • Executive Editor: Ms. Nina Lee
    • Abstracting/ Indexing: EI (INSPEC, IET),  Electronic Journals Library, Ulrich's Periodicals Directory, EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
Dr. Ka Wai Gary Wong
Division of Information and Technology Studies, Faculty of Education, The University of Hong Kong.
It's a honor to serve as the editor-in-chief of JACN. I'll work together with the editors and reviewers to help the journal progress
JACN 2015 Vol.3(3): 180-185 ISSN: 1793-8244
DOI: 10.7763/JACN.2015.V3.163

Processing of Cryptographic Function Identification Based on Multi-feature Progressive Model

Wei Lin, Yuefei Zhu, and Ruijie Cai
Abstract—Research on cryptographic function identification is of great significance in malicious code analysis, software vulnerability analysis and other fields. The current cryptographic function identification algorithm has the problem of low identification accuracy because of its single feature. In order to solve this problem, we proposed an improved method of cryptographic function identification based on multi-feature progressive approach to identify cryptographic functions by using data flow analysis in software. The experimental results show that, compared to current methods, it can identify the accurate cryptographic function accurately, and the accuracy is improved.

Index Terms—Cryptographic function identification, multi-feature matching, progressive, decision tree, data flow analysis.

The authors are with the State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, P. R. China (e-mail: tiamo9880@gmail.com, zyf0136@sina.com, wsxcrj@163.com).


Cite:Wei Lin, Yuefei Zhu, and Ruijie Cai, "Processing of Cryptographic Function Identification Based on Multi-feature Progressive Model," Journal of Advances in Computer Networks vol. 3, no. 3, pp. 180-185, 2015.

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