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Wild Networks: Exposure of 5G Network Infrastructures to Adversarial
  Examples

Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples

4 July 2022
Giovanni Apruzzese
Rodion Vladimirov
A.T. Tastemirova
P. Laskov
    AAML
ArXivPDFHTML

Papers citing "Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples"

6 / 6 papers shown
Title
"Real Attackers Don't Compute Gradients": Bridging the Gap Between
  Adversarial ML Research and Practice
"Real Attackers Don't Compute Gradients": Bridging the Gap Between Adversarial ML Research and Practice
Giovanni Apruzzese
Hyrum S. Anderson
Savino Dambra
D. Freeman
Fabio Pierazzi
Kevin A. Roundy
AAML
24
75
0
29 Dec 2022
From NEA and NIA to NESAS and SCAS: Demystifying the 5G Security
  Ecosystem
From NEA and NIA to NESAS and SCAS: Demystifying the 5G Security Ecosystem
A. Michalas
Constantinos Patsakis
D. Vergados
D. Vergados
18
1
0
18 Dec 2022
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Poisoning the Unlabeled Dataset of Semi-Supervised Learning
Nicholas Carlini
AAML
139
68
0
04 May 2021
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks
Backdooring and Poisoning Neural Networks with Image-Scaling Attacks
Erwin Quiring
Konrad Rieck
AAML
46
70
0
19 Mar 2020
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation
  Classifier over Wireless Channels
Over-the-Air Adversarial Attacks on Deep Learning Based Modulation Classifier over Wireless Channels
Brian Kim
Y. Sagduyu
Kemal Davaslioglu
T. Erpek
S. Ulukus
AAML
38
68
0
05 Feb 2020
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
250
5,830
0
08 Jul 2016
1