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Adaptive Randomized Smoothing: Certifying Multi-Step Defences against
  Adversarial Examples

Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples

14 June 2024
Saiyue Lyu
Shadab Shaikh
Frederick Shpilevskiy
Evan Shelhamer
Mathias Lécuyer
    AAML
ArXiv (abs)PDFHTML

Papers citing "Adaptive Randomized Smoothing: Certifying Multi-Step Defences against Adversarial Examples"

18 / 18 papers shown
Title
UniCR: Universally Approximated Certified Robustness via Randomized
  Smoothing
UniCR: Universally Approximated Certified Robustness via Randomized Smoothing
Hanbin Hong
Binghui Wang
Yuan Hong
AAML
76
11
0
05 Jul 2022
Double Sampling Randomized Smoothing
Double Sampling Randomized Smoothing
Linyi Li
Jiawei Zhang
Tao Xie
Yue Liu
AAML
77
25
0
16 Jun 2022
Diffusion Models for Adversarial Purification
Diffusion Models for Adversarial Purification
Weili Nie
Brandon Guo
Yujia Huang
Chaowei Xiao
Arash Vahdat
Anima Anandkumar
WIGM
269
450
0
16 May 2022
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Evaluating the Adversarial Robustness of Adaptive Test-time Defenses
Francesco Croce
Sven Gowal
T. Brunner
Evan Shelhamer
Matthias Hein
A. Cemgil
TTAAAML
231
70
0
28 Feb 2022
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
AID-Purifier: A Light Auxiliary Network for Boosting Adversarial Defense
Duhun Hwang
Eunjung Lee
Wonjong Rhee
AAML
208
16
0
14 Jul 2021
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion
  based Perception in Autonomous Driving Under Physical-World Attacks
Invisible for both Camera and LiDAR: Security of Multi-Sensor Fusion based Perception in Autonomous Driving Under Physical-World Attacks
Yulong Cao*
Ningfei Wang*
Chaowei Xiao
Dawei Yang
Jin Fang
Ruigang Yang
Qi Alfred Chen
Mingyan D. Liu
Yue Liu
AAML
98
225
0
17 Jun 2021
Adversarial purification with Score-based generative models
Adversarial purification with Score-based generative models
Jongmin Yoon
Sung Ju Hwang
Juho Lee
DiffM
90
158
0
11 Jun 2021
Numerical Composition of Differential Privacy
Numerical Composition of Differential Privacy
Sivakanth Gopi
Y. Lee
Lukas Wutschitz
77
183
0
05 Jun 2021
Combating Adversaries with Anti-Adversaries
Combating Adversaries with Anti-Adversaries
Motasem Alfarra
Juan C. Pérez
Ali K. Thabet
Adel Bibi
Philip Torr
Guohao Li
AAML
83
27
0
26 Mar 2021
Adversarial Attacks are Reversible with Natural Supervision
Adversarial Attacks are Reversible with Natural Supervision
Chengzhi Mao
Mia Chiquer
Hao Wang
Junfeng Yang
Carl Vondrick
BDLAAML
86
56
0
26 Mar 2021
Data-Dependent Randomized Smoothing
Data-Dependent Randomized Smoothing
Motasem Alfarra
Adel Bibi
Philip Torr
Guohao Li
UQCV
77
35
0
08 Dec 2020
Bridging Composite and Real: Towards End-to-end Deep Image Matting
Bridging Composite and Real: Towards End-to-end Deep Image Matting
Jizhizi Li
Jing Zhang
Stephen J. Maybank
Dacheng Tao
77
118
0
30 Oct 2020
On Adaptive Attacks to Adversarial Example Defenses
On Adaptive Attacks to Adversarial Example Defenses
Florian Tramèr
Nicholas Carlini
Wieland Brendel
Aleksander Madry
AAML
285
839
0
19 Feb 2020
Provably Robust Deep Learning via Adversarially Trained Smoothed
  Classifiers
Provably Robust Deep Learning via Adversarially Trained Smoothed Classifiers
Hadi Salman
Greg Yang
Jungshian Li
Pengchuan Zhang
Huan Zhang
Ilya P. Razenshteyn
Sébastien Bubeck
AAML
90
552
0
09 Jun 2019
Certified Adversarial Robustness via Randomized Smoothing
Certified Adversarial Robustness via Randomized Smoothing
Jeremy M. Cohen
Elan Rosenfeld
J. Zico Kolter
AAML
169
2,052
0
08 Feb 2019
Adversarial Attacks and Defences: A Survey
Adversarial Attacks and Defences: A Survey
Anirban Chakraborty
Manaar Alam
Vishal Dey
Anupam Chattopadhyay
Debdeep Mukhopadhyay
AAMLOOD
89
683
0
28 Sep 2018
Certified Robustness to Adversarial Examples with Differential Privacy
Certified Robustness to Adversarial Examples with Differential Privacy
Mathias Lécuyer
Vaggelis Atlidakis
Roxana Geambasu
Daniel J. Hsu
Suman Jana
SILMAAML
96
939
0
09 Feb 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing
  Defenses to Adversarial Examples
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
Anish Athalye
Nicholas Carlini
D. Wagner
AAML
243
3,194
0
01 Feb 2018
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