Clustering versus SVM for malware detection-Reference-Cited by-同舟云学术

Clustering versus SVM for malware detection

Published:2015-10-03 Issue:4 Volume:12 Page:213-224
ISSN:2263-8733
Container-title:Journal of Computer Virology and Hacking Techniques
language:en
Short-container-title:J Comput Virol Hack Tech

Author:

Narra Usha,Troia Fabio Di,Corrado Visaggio Aaron,Austin Thomas H.,Stamp Mark

Publisher

Springer Science and Business Media LLC

Subject

Computational Theory and Mathematics,Hardware and Architecture,Software,Computer Science (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s11416-015-0253-z.pdf

Reference31 articles.

1. Alsabti, K., Ranka, S., Singh, V.: An efficient K-means clustering algorithm. https://www.cs.utexas.edu/~kuipers/readings/Alsabti-hpdm-98.pdf (1998). Accessed 22 Sept 2015

2. Annachhatre, C., Austin, T.H., Stamp, M.: HiddenMarkov models for malware classification. J. Comput. Virol. Hack. Tech. 11(2), 59–73 (2014)

3. Austin, T., Filiol, E., Josse, S., Stamp, M.: Exploring hidden Markov models for virus analysis: a semantic approach. In: 46th Hawaii International Conference on System Sciences (HICSS 2013), pp. 5039–5048 (2013)

4. Baysa, D., Low, R.M., Stamp, M.: Structural entropy and metamorphic malware. J. Comput. Virol. Hack. Tech. 9(4), 179–192 (2013)

5. Bilmes, J.A.: A Gentle tutorial of the EM algorithm and its application to parameter estimation for Gaussian mixture and hidden Markov models. http://crow.ee.washington.edu/people/bulyko/papers/em.pdf (1998). Accessed 22 Sept 2015

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