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General Information
    • ISSN: 1793-8244 (Print)
    • Abbreviated Title:  J. Adv. Comput. Netw.
    • Frequency: Semiyearly
    • DOI: 10.18178/JACN
    • Editor-in-Chief: Professor Haklin Kimm
    • Executive Editor: Ms. Cherry Chan
    • Abstracting/ Indexing: EBSCO, ProQuest, and Google Scholar.
    • E-mail: jacn@ejournal.net
    • APC: 500USD
Professor Haklin Kimm
East Stroudsburg University, USA
I'm happy to take on the position of editor in chief of JACN. We encourage authors to submit papers on all aspects of computer networks.

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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