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MLHat (Workshop) (2020 :)

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Deployable machine learning for security defense = first International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020 : proceedings /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Deployable machine learning for security defense/ edited by Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh.
Reminder of title:	first International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020 : proceedings /
remainder title:	MLHat 2020
other author:	Wang, Gang.
corporate name:	MLHat (Workshop)
Published:	Cham :Springer International Publishing : : 2020.,
Description:	vii, 165 p. :ill., digital ;24 cm.
[NT 15003449]:	Understanding the Adversaries -- Adversarial ML for Better Security -- Threats on Networks.
Contained By:	Springer Nature eBook
Subject:	Machine learning - Congresses. -
Online resource:	https://doi.org/10.1007/978-3-030-59621-7
ISBN:	9783030596217

Deployable machine learning for security defense = first International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020 : proceedings /
Deployable machine learning for security defensefirst International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020 : proceedings /[electronic resource] :MLHat 2020edited by Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh. - Cham :Springer International Publishing :2020. - vii, 165 p. :ill., digital ;24 cm. - Communications in computer and information science,12711865-0929 ;. - Communications in computer and information science ;1271..

Understanding the Adversaries -- Adversarial ML for Better Security -- Threats on Networks.

This book constitutes selected papers from the First International Workshop on Deployable Machine Learning for Security Defense, MLHat 2020, held in August 2020. Due to the COVID-19 pandemic the conference was held online. 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.

ISBN: 9783030596217

Standard No.: 10.1007/978-3-030-59621-7doiSubjects--Topical Terms:

576368
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Deployable machine learning for security defense = first International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020 : proceedings /
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