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Revealing Perceptible Backdoors, without the Training Set, via the
  Maximum Achievable Misclassification Fraction Statistic

Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic

18 November 2019
Zhen Xiang
David J. Miller
Hang Wang
G. Kesidis
    AAML
ArXivPDFHTML

Papers citing "Revealing Perceptible Backdoors, without the Training Set, via the Maximum Achievable Misclassification Fraction Statistic"

4 / 4 papers shown
Title
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?
How to Sift Out a Clean Data Subset in the Presence of Data Poisoning?
Yi Zeng
Minzhou Pan
Himanshu Jahagirdar
Ming Jin
Lingjuan Lyu
R. Jia
AAML
39
21
0
12 Oct 2022
Detecting Backdoor Attacks Against Point Cloud Classifiers
Detecting Backdoor Attacks Against Point Cloud Classifiers
Zhen Xiang
David J. Miller
Siheng Chen
Xi Li
G. Kesidis
3DPC
AAML
40
15
0
20 Oct 2021
A Backdoor Attack against 3D Point Cloud Classifiers
A Backdoor Attack against 3D Point Cloud Classifiers
Zhen Xiang
David J. Miller
Siheng Chen
Xi Li
G. Kesidis
3DPC
AAML
33
76
0
12 Apr 2021
Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural
  Networks for Detection and Training Set Cleansing
Reverse Engineering Imperceptible Backdoor Attacks on Deep Neural Networks for Detection and Training Set Cleansing
Zhen Xiang
David J. Miller
G. Kesidis
35
22
0
15 Oct 2020
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