Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks

Back in Black: A Comparative Evaluation of Recent State-Of-The-Art Black-Box Attacks

The field of adversarial machine learning has experienced a near exponential growth in the amount of papers being produced since 2018. This massive information output has yet to be properly processed and categorized. In this paper, we seek to help alleviate this problem by systematizing the recent a...

Full description

Bibliographic Details
Main Authors: Kaleel Mahmood, Rigel Mahmood, Ethan Rathbun, Marten van Dijk
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Adversarial machine learning
adversarial examples
adversarial defense
black-box attack
security
deep learning
Online Access:https://ieeexplore.ieee.org/document/9663183/

Internet

https://ieeexplore.ieee.org/document/9663183/

Similar Items