Evade Hard Multiple Classifier Systems-Reference-Cited by-同舟云学术

Evade Hard Multiple Classifier Systems

Published:2009 Issue: Volume: Page:15-38
ISSN:1860-949X
Container-title:Studies in Computational Intelligence
language:
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Author:

Biggio Battista,Fumera Giorgio,Roli Fabio

Publisher

Springer Berlin Heidelberg

Link

http://link.springer.com/content/pdf/10.1007/978-3-642-03999-7_2.pdf

Reference11 articles.

1. Barreno, M., Nelson, B., Sears, R., Joseph, A.D., Tygar, J.D.: Can machine learning be secure? In: Proc. 2006 ACM Symp. Inf., Computer and Communications Security, Taipei, Taiwan, pp. 16–25. ACM, New York (2006)

2. Chang, C.C., Lin, C.J.: LIBSVM: a library for support vector machines (2001), http://www.csie.ntu.edu.tw/~cjlin/libsvm

3. Dalvi, N., Domingos, P., Mausam, S.S., Verma, D.: Adversarial classification. In: Proc. 10th ACM SIGKDD Int. Conf. Knowledge Discovery and Data Mining, Seattle, WA, pp. 99–108. ACM, New York (2004)

4. Giacinto, G., Roli, F., Didaci, L.: Fusion of multiple classifiers for intrusion detection in computer networks. Pattern Recognition Letters 24(12), 1795–1803 (2003)

5. Globerson, A., Roweis, S.T.: Nightmare at test time: robust learning by feature deletion. In: Cohen, W.W., Moore, A. (eds.) Proc. 23rd Int. Conf. Mach. Learn., Pittsburgh, PA, pp. 353–360. ACM, New York (2006)

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