Deployable Machine Learning for Security Defense
First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings
(Sprache: Englisch)
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...
The 8 full papers were...
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Klappentext zu „Deployable Machine Learning for Security Defense “
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.
Inhaltsverzeichnis zu „Deployable Machine Learning for Security Defense “
Understanding the Adversaries.- Adversarial ML for Better Security.- Threats on Networks.
Bibliographische Angaben
- 2020, 1st ed. 2020, VII, 165 Seiten, 45 farbige Abbildungen, Maße: 15,6 x 23,6 cm, Kartoniert (TB), Englisch
- Herausgegeben: Gang Wang, Arridhana Ciptadi, Ali Ahmadzadeh
- Verlag: Springer, Berlin
- ISBN-10: 3030596206
- ISBN-13: 9783030596200
Sprache:
Englisch
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