Analyzing File-to-File Relation Network in Malware Detection-Reference-Cited by-同舟云学术

Analyzing File-to-File Relation Network in Malware Detection

Published:2015 Issue: Volume: Page:415-430
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
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Author:

Chen Lingwei,Hardy William,Ye Yanfang,Li Tao

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-26190-4_28

Reference30 articles.

1. Lecture Notes in Computer Science;M Bailey,2007

2. Chau, D., Nachenberg, C., Wilhelm, J., Wright, A., Faloutsos, C.: Polonium: tera-scale graph mining for malware detection. In: SIAM International Conference on Data Mining (SDM), pp. 131–142 (2011)

3. Chen, L., Li, T., Abdulhayoglu, M., Ye, Y.: Intelligent malware detection based on file relation graphs. In: 9th IEEE International Conference on Sematic Computing, pp. 85–92 (2015)

4. Chen, K., Zhu, P., Xiong, Y.: Mining spam accounts with user influence. In: International Conference on ISCC-C, pp. 167–173 (2013)

5. Computer Security Institute: 12th annual edition of the CSI computer crime and security survey. Technical report, Computer Security Institute (2007)

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