Practical Adversarial Attacks Against AI-Driven Power Allocation in a Distributed MIMO Network
Author:
Affiliation:
1. Ericsson Research,Istanbul,Turkey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10278505/10278554/10278572.pdf?arnumber=10278572
Reference13 articles.
1. Universal Adversarial Attacks on Neural Networks for Power Allocation in a Massive MIMO System
2. Univer-sal adversarial perturbations;moosavi-dezfooli;Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR),2017
3. Practical Black-Box Attacks against Machine Learning
4. Adversarial Examples in the Physical World
5. Foundations of User-Centric Cell-Free Massive MIMO
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Security of AI-Driven Beam Selection for Distributed MIMO in an Adversarial Setting;IEEE Access;2024
2. A Novel Method to Mitigate Adversarial Attacks on AI-Driven Power Allocation in D-MIMO;2023 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom);2023-07-04
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