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A Hybrid Training-time and Run-time Defense Against Adversarial Attacks
  in Modulation Classification

A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification

9 July 2024
Lu Zhang
S. Lambotharan
G. Zheng
G. Liao
Ambra Demontis
Fabio Roli
    AAML
ArXiv (abs)PDFHTML

Papers citing "A Hybrid Training-time and Run-time Defense Against Adversarial Attacks in Modulation Classification"

4 / 4 papers shown
Title
A Novel and Practical Universal Adversarial Perturbations against Deep Reinforcement Learning based Intrusion Detection Systems
A Novel and Practical Universal Adversarial Perturbations against Deep Reinforcement Learning based Intrusion Detection Systems
H. Zhang
Liyue Zhang
G. Epiphaniou
C. Maple
AAML
76
0
0
22 Nov 2025
Meta-Learning Guided Label Noise Distillation for Robust Signal
  Modulation Classification
Meta-Learning Guided Label Noise Distillation for Robust Signal Modulation ClassificationIEEE Internet of Things Journal (IEEE IoT J.), 2024
Xiaoyang Hao
Zhixi Feng
Tongqing Peng
Shuyuan Yang
NoLa
171
18
0
09 Aug 2024
Data-Driven Subsampling in the Presence of an Adversarial Actor
Data-Driven Subsampling in the Presence of an Adversarial Actor
Abu Shafin Mohammad Mahdee Jameel
Ahmed P. Mohamed
Jinho Yi
Aly El Gamal
Akshay Malhotra
99
0
0
07 Jan 2024
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A
  Contemporary Survey
Adversarial Attacks and Defenses in Machine Learning-Powered Networks: A Contemporary Survey
Yulong Wang
Tong Sun
Shenghong Li
Xinnan Yuan
W. Ni
Ekram Hossain
H. Vincent Poor
AAML
239
28
0
11 Mar 2023
1