Výsledky vyhledávání - "Xiao-chun Yun"

Akademický článek

Fast reused code tracing method based on simhash and inverted index

Autor: Yan-chen QIAO, Xiao-chun YUN, Yu-peng TUO, Yong-zheng ZHANG

Publikováno v: Tongxin xuebao, Vol 37, Pp 104-113 (2016)

A novel method for fast and accurately tracing reused code was proposed. Based on simhash and inverted in-dex, the method can fast trace similar functions in massive code. First of all, a code database with three-level inverted in-dex structures was

Externí odkaz: https://doaj.org/article/7c58aba5ead7432997a82eee93414e1c

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Akademický článek

CBFM:cutted Bloom filter matrix for multi-dimensional membership query

Autor: Yong WANG, Xiao-chun YUN, ANGShu-peng WANG, Xi WANG

Publikováno v: Tongxin xuebao, Vol 37, Pp 139-147 (2016)

In order to improve the flexibility and accuracy of mu i-dimensional membership query,a new indexing structure called CBFM(cutted Bloom filter matrix)was proposed.CBFM built the bit matrix by the Cartesian product of different bloom filters,each repr

Externí odkaz: https://doaj.org/article/36d1bbfc4b2346cfa03c61887bb04633

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Akademický článek

Network protocol identification based on active learning and SVM algorithm

Autor: Yi-peng WANG, Xiao-chun YUN, Yong-zheng ZHANG, Shu-hao LI

Publikováno v: Tongxin xuebao, Vol 34, Pp 135-142 (2013)

Obtaining qualified training data for protocol identif ion generally requires domain experts to be involved,which is time-consuming and laborious.A novel approach for network protocol identification based on active learning and SVM algorithm was prop

Externí odkaz: https://doaj.org/article/bffccc76e2fd4b5f836a714017105cdc

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Akademický článek

Online analytical model of massive malware based on feature clusting

Autor: Xiao-lin XU, Xiao-chun YUN, Yong-lin ZHOU, Xue-bin KANG

Publikováno v: Tongxin xuebao, Vol 34, Pp 146-153 (2013)

In order to improve the effectiveness and efficiency of mass malicious code analysis,an online analytical model was proposed including feature space construction,automatic feature extraction and fast clustering.Our research focused on the law of malw

Externí odkaz: https://doaj.org/article/9e46c3b75e1e48cfa4cc85c8a027b7a8

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