Deployable Machine Learning for Security Defense - First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings (Paperback, 1st ed. 2020)

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.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Communications in Computer and Information Science, 1271
Release date:	October 2020
First published:	2020
Editors:	Gang Wang • Arridhana Ciptadi • Ali Ahmadzadeh
Dimensions:	235 x 155mm (L x W)
Format:	Paperback
Pages:	165
Edition:	1st ed. 2020
ISBN-13:	978-3-03-059620-0
Categories:	Books > Computing & IT > General theory of computing > General Books > Computing & IT > Computer communications & networking > Network security Books > Computing & IT > Internet > Network computers Books > Computing & IT > Social & legal aspects of computing > Computer fraud & hacking Books > Computing & IT > Applications of computing > Databases > General Books > Computing & IT > Applications of computing > Artificial intelligence > General
LSN:	3-03-059620-6
Barcode:	9783030596200

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