Deployable Machine Learning for Security Defense First International Workshop, MLHat 2020, San Diego, CA, USA, August 24, 2020, Proceedings /
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 sub...
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| Other Authors: | , , |
| Language: | English |
| Published: |
Cham :
Springer International Publishing : Imprint: Springer,
2020.
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| Edition: | 1st ed. 2020. |
| Series: | Communications in Computer and Information Science,
1271 |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/978-3-030-59621-7 |
| Summary: | 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. |
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| Physical Description: | VII, 165 p. 170 illus., 45 illus. in color. online resource. |
| ISBN: | 9783030596217 |
| ISSN: | 1865-0929 ; |