A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf
.
A Generative Model based Adversarial Security of Deep Learning and Linear Classifier Models
[article]
2020
arXiv
pre-print
In recent years, machine learning algorithms have been applied widely in various fields such as health, transportation, and the autonomous car. With the rapid developments of deep learning techniques, it is critical to take the security concern into account for the application of the algorithms. While machine learning offers significant advantages in terms of the application of algorithms, the issue of security is ignored. Since it has many applications in the real world, security is a vital
arXiv:2010.08546v1
fatcat:trqowc5b5jbnvaqvgafyiui76m