Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction

9 May 2021

Papers citing "Security Concerns on Machine Learning Solutions for 6G Networks in mmWave Beam Prediction"

8 / 8 papers shown

Title
Adversarial Security and Differential Privacy in mmWave Beam Prediction in 6G networks G. S. Krishna Kundrapu Supriya Sanskar Singh S. Baidya AAML 6 0 0 12 May 2023
A Streamlit-based Artificial Intelligence Trust Platform for Next-Generation Wireless Networks Murat Kuzlu Ferhat Ozgur Catak S. Sarp U. Cali O. Gueler 9 8 0 25 Oct 2022
Mitigating Attacks on Artificial Intelligence-based Spectrum Sensing for Cellular Network Signals Ferhat Ozgur Catak Murat Kuzlu S. Sarp Evren Çatak Umit Cali AAML 11 3 0 27 Sep 2022
Defensive Distillation based Adversarial Attacks Mitigation Method for Channel Estimation using Deep Learning Models in Next-Generation Wireless Networks Ferhat Ozgur Catak Murat Kuzlu Evren Çatak Umit Cali Ozgur Guler AAML 9 24 0 12 Aug 2022
The Adversarial Security Mitigations of mmWave Beamforming Prediction Models using Defensive Distillation and Adversarial Retraining Murat Kuzlu Ferhat Ozgur Catak Umit Cali Evren Çatak Ozgur Guler AAML 11 9 0 16 Feb 2022
Recent Advances in Adversarial Training for Adversarial Robustness Tao Bai Jinqi Luo Jun Zhao B. Wen Qian Wang AAML 71 473 0 02 Feb 2021
Context-Aware Security for 6G Wireless The Role of Physical Layer Security A. Chorti A. Barreto Stefan Kopsell M. Zoli Marwa Chafii P. Sehier G. Fettweis H. Vincent Poor 31 123 0 05 Jan 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,108 0 04 Nov 2016