Deployable Machine Learning for Security Defense
Author | : Gang Wang |
Publisher | : Springer Nature |
Total Pages | : 168 |
Release | : 2020-10-17 |
ISBN-10 | : 9783030596217 |
ISBN-13 | : 3030596214 |
Rating | : 4/5 (17 Downloads) |
Download or read book Deployable Machine Learning for Security Defense written by Gang Wang and published by Springer Nature. This book was released on 2020-10-17 with total page 168 pages. Available in PDF, EPUB and Kindle. 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.