Deployable Machine Learning for Security Defense
Download or Read eBook Deployable Machine Learning for Security Defense PDF written by Gang Wang and published by Springer Nature. This book was released on 2020-10-17 with total page 165 pages. Available in PDF, EPUB and Kindle.
| Author | : Gang Wang |
| Publisher | : Springer Nature |
| Total Pages | : 165 |
| Release | : 2020-10-17 |
| ISBN-10 | : 9783030596217 |
| ISBN-13 | : 3030596214 |
| Rating | : 4/5 (17 Downloads) |
Book Synopsis Deployable Machine Learning for Security Defense by : Gang Wang
Book excerpt: 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.
