Hidden Markov models with random restarts versus boosting for malware detection-Reference-Cited by-同舟云学术

Hidden Markov models with random restarts versus boosting for malware detection

Published:2018-08-28 Issue:2 Volume:15 Page:97-107
ISSN:2263-8733
Container-title:Journal of Computer Virology and Hacking Techniques
language:en
Short-container-title:J Comput Virol Hack Tech

Author:

Raghavan Aditya,Di Troia Fabio,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/s11416-018-0322-1.pdf

Reference48 articles.

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2. Annachhatre, C., Austin, T.H., Stamp, M.: Hidden Markov models for malware classification. J. Comput. Virol. Hacking Tech. 11(2), 59–73 (2015)

3. Ariu, D., Tronci, R., Giacinto, G.: HMMPayl: an intrusion detection system based on hidden Markov models. Comput. Secur. 30(4), 221–241 (2011)

4. Austin, T.H., Filiol, E., Josse, S., Stamp, M.: Exploring hidden Markov models for virus analysis: a semantic approach. In: Proceedings of the 2013 46th Hawaii International Conference on System Sciences, HICSS ’13, pp. 5039–5048. IEEE Computer Society (2013)

5. Aycock, J.: Computer viruses and malware. In: Jajodia, S. (ed.) Advances in Information Security. Springer, US (2006)

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