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Abstract:
Differing in traditional methods which extracted too much features or filtered valuable items, we proposed a feature representation and extraction method based on LZW compression algorithm to detect malicious codes. The compression algorithm not only reduces the number of features, but also is enough to cover malicious codes. In this paper, we described the process of our feature extraction in detail, including 0-data processing, fix-length coding and threshold setting. The experimental results show that our method outperforms other methods based on Bayes and SVM in DR and AR. © 2013 Springer-Verlag GmbH.
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ISSN: 1876-1100
Year: 2013
Issue: VOL. 1
Volume: 156 LNEE
Page: 211-218
Language: English
Cited Count:
WoS CC Cited Count: 0
SCOPUS Cited Count:
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 9
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