Editors:
Part of the book series: Communications in Computer and Information Science (CCIS, volume 1271)
Conference series link(s): MLHat: International Workshop on Deployable Machine Learning for Security Defense
Conference proceedings info: MLHat 2020.
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Table of contents (8 papers)
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Front Matter
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Understanding the Adversaries
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Front Matter
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Adversarial ML for Better Security
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Front Matter
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Back Matter
About this book
The 8 full papers were thoroughly reviewed and selected from 13 qualified submissions. The papers are organized in the following topical sections: understanding the adversaries; adversarial ML for better security; threats on networks.
Editors and Affiliations
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University of Illinois at Urbana Champaign, Urbana, USA
Gang Wang
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Blue Hexagon Inc., Sunnyvale, USA
Arridhana Ciptadi, Ali Ahmadzadeh
Bibliographic Information
Book Title: Deployable Machine Learning for Security Defense
Book Subtitle: First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings
Editors: Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh
Series Title: Communications in Computer and Information Science
DOI: https://doi.org/10.1007/978-3-030-59621-7
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2020
Softcover ISBN: 978-3-030-59620-0Published: 18 October 2020
eBook ISBN: 978-3-030-59621-7Published: 17 October 2020
Series ISSN: 1865-0929
Series E-ISSN: 1865-0937
Edition Number: 1
Number of Pages: VII, 165
Number of Illustrations: 125 b/w illustrations, 45 illustrations in colour
Topics: Computing Milieux, Systems and Data Security, Computer Crime, Artificial Intelligence, Computer Communication Networks, Information Systems Applications (incl. Internet)