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When Attackers Meet AI: Learning-empowered Attacks in Cooperative
  Spectrum Sensing
v1v2 (latest)

When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing

4 May 2019
Z. Luo
Shangqing Zhao
Zhuo Lu
Jie Xu
Y. Sagduyu
    AAML
ArXiv (abs)PDFHTML

Papers citing "When Attackers Meet AI: Learning-empowered Attacks in Cooperative Spectrum Sensing"

16 / 16 papers shown
Title
Detecting Adversarial Spectrum Attacks via Distance to Decision Boundary
  Statistics
Detecting Adversarial Spectrum Attacks via Distance to Decision Boundary Statistics
Wenwei Zhao
Xiaowen Li
Shangqing Zhao
Jie Xu
Yao-Hong Liu
Zhuo Lu
AAML
49
1
0
14 Feb 2024
Securing NextG Systems against Poisoning Attacks on Federated Learning:
  A Game-Theoretic Solution
Securing NextG Systems against Poisoning Attacks on Federated Learning: A Game-Theoretic Solution
Y. Sagduyu
T. Erpek
Yi Shi
AAML
67
2
0
28 Dec 2023
AIR: Threats of Adversarial Attacks on Deep Learning-Based Information
  Recovery
AIR: Threats of Adversarial Attacks on Deep Learning-Based Information Recovery
Jinyin Chen
Jie Ge
Shilian Zheng
Linhui Ye
Haibin Zheng
Weiguo Shen
Keqiang Yue
Xiaoniu Yang
AAML
49
2
0
17 Aug 2023
Adversarial Machine Learning and Defense Game for NextG Signal
  Classification with Deep Learning
Adversarial Machine Learning and Defense Game for NextG Signal Classification with Deep Learning
Y. Sagduyu
AAML
50
2
0
22 Dec 2022
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial
  Examples
Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples
Giovanni Apruzzese
Rodion Vladimirov
A.T. Tastemirova
Pavel Laskov
AAML
100
16
0
04 Jul 2022
SecureSense: Defending Adversarial Attack for Secure Device-Free Human
  Activity Recognition
SecureSense: Defending Adversarial Attack for Secure Device-Free Human Activity Recognition
Jianfei Yang
Han Zou
Lihua Xie
AAMLHAI
86
20
0
04 Apr 2022
Machine Learning in NextG Networks via Generative Adversarial Networks
Machine Learning in NextG Networks via Generative Adversarial Networks
E. Ayanoglu
Kemal Davaslioglu
Y. Sagduyu
GAN
65
34
0
09 Mar 2022
Jamming Attacks on Federated Learning in Wireless Networks
Jamming Attacks on Federated Learning in Wireless Networks
Yi Shi
Y. Sagduyu
93
12
0
13 Jan 2022
When Machine Learning Meets Spectrum Sharing Security: Methodologies and
  Challenges
When Machine Learning Meets Spectrum Sharing Security: Methodologies and Challenges
Qun Wang
Haijian Sun
R. Hu
Arupjyoti Bhuyan
81
24
0
12 Jan 2022
Adversarial Attacks against Deep Learning Based Power Control in
  Wireless Communications
Adversarial Attacks against Deep Learning Based Power Control in Wireless Communications
Brian Kim
Yi Shi
Y. Sagduyu
T. Erpek
S. Ulukus
AAML
83
27
0
16 Sep 2021
Membership Inference Attack and Defense for Wireless Signal Classifiers
  with Deep Learning
Membership Inference Attack and Defense for Wireless Signal Classifiers with Deep Learning
Yi Shi
Y. Sagduyu
78
17
0
22 Jul 2021
Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G
  and Beyond
Adversarial Attacks on Deep Learning Based mmWave Beam Prediction in 5G and Beyond
Brian Kim
Y. Sagduyu
T. Erpek
S. Ulukus
AAML
78
23
0
25 Mar 2021
Adversarial Machine Learning for 5G Communications Security
Adversarial Machine Learning for 5G Communications Security
Y. Sagduyu
T. Erpek
Yi Shi
AAML
85
43
0
07 Jan 2021
How to Make 5G Communications "Invisible": Adversarial Machine Learning
  for Wireless Privacy
How to Make 5G Communications "Invisible": Adversarial Machine Learning for Wireless Privacy
Brian Kim
Y. Sagduyu
Kemal Davaslioglu
T. Erpek
S. Ulukus
AAML
51
29
0
15 May 2020
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless
  Signal Classifiers
Channel-Aware Adversarial Attacks Against Deep Learning-Based Wireless Signal Classifiers
Brian Kim
Y. Sagduyu
Kemal Davaslioglu
T. Erpek
S. Ulukus
AAML
89
119
0
11 May 2020
When Wireless Security Meets Machine Learning: Motivation, Challenges,
  and Research Directions
When Wireless Security Meets Machine Learning: Motivation, Challenges, and Research Directions
Y. Sagduyu
Yi Shi
T. Erpek
William C. Headley
Bryse Flowers
G. Stantchev
Zhuo Lu
AAML
73
39
0
24 Jan 2020
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