Detecting machine-morphed malware variants via engine attribution-Reference-Cited by-同舟云学术

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Detecting machine-morphed malware variants via engine attribution

Published:2013-03-05 Issue:3 Volume:9 Page:137-157
ISSN:2263-8733
Container-title:Journal of Computer Virology and Hacking Techniques
language:en
Short-container-title:J Comput Virol Hack Tech

Author:

Chouchane Radhouane,Stakhanova Natalia,Walenstein Andrew,Lakhotia Arun

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/s11416-013-0183-6.pdf

Reference83 articles.

1. Abou-Assaleh, T., Cercone, N., Kešelj, V., Sweidan, R.: N-gram-based detection of new malicious code. In: 28th Annual IEEE International Computer Software and Applications Conference, pp. 41–42 (2004)

2. Argamon, S., Koppel, M., Pennebaker, J.W., Schler, J.: Automatically profiling the author of an anonymous text. Commun. ACM 52(2), 119–123 (2009)

3. Babić, D., Reynaud, D., Song, D.: Malware analysis with tree automata inference. In: Proceedings of the 23rd International Conference on Computer Aided Verification (CAV), pp. 116–131. Snowbird, UT (2011)

4. Bilar, D.: Opcodes as predictor for malware. Int. J. Electron. Secur. Digit. Forensics 1(2), 156–168 (2007)

5. Bonfante, G., Kaczmarek, M., Marion, J.Y.: Architecture of a morphological malware detector. J. Comput. Virol. 5(3), 263–270 (2009)

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