Is data clustering in adversarial settings secure?-Reference-Cited by-同舟云学术

Is data clustering in adversarial settings secure?

Published:2013-11-04 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2013 ACM workshop on Artificial intelligence and security
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Author:

Biggio Battista¹,Pillai Ignazio¹,Rota Bulò Samuel²,Ariu Davide¹,Pelillo Marcello³,Roli Fabio¹

Affiliation:

1. Università di Cagliari, Cagliari, Italy

2. FBK-irst, Trento, Italy

3. Università Ca' Foscari di Venezia, Venice, Italy

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/2517312.2517321

Reference30 articles.

1. Collaborative Malware Collection and Sensing. https://alliance.mwcollect.org. Collaborative Malware Collection and Sensing. https://alliance.mwcollect.org.

2. Project Malfease. http://malfease.oarci.net. Project Malfease. http://malfease.oarci.net.

3. Can machine learning be secure?

4. B. Biggio G. Fumera and F. Roli. Design of robust classifiers for adversarial environments. In IEEE Int'l Conf. on Systems Man and Cybernetics (SMC) pages 977--982 2011. B. Biggio G. Fumera and F. Roli. Design of robust classifiers for adversarial environments. In IEEE Int'l Conf. on Systems Man and Cybernetics (SMC) pages 977--982 2011.

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