ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 1903.10586
  4. Cited By
Defending against Whitebox Adversarial Attacks via Randomized
  Discretization

Defending against Whitebox Adversarial Attacks via Randomized Discretization

25 March 2019
Yuchen Zhang
Percy Liang
    AAML
ArXivPDFHTML

Papers citing "Defending against Whitebox Adversarial Attacks via Randomized Discretization"

14 / 14 papers shown
Title
Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics
Exploring the Adversarial Vulnerabilities of Vision-Language-Action Models in Robotics
Taowen Wang
Dongfang Liu
James Liang
Wenhao Yang
Qifan Wang
Cheng Han
Jiebo Luo
Ruixiang Tang
Ruixiang Tang
AAML
74
3
0
18 Nov 2024
SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation
SAAM: Stealthy Adversarial Attack on Monocular Depth Estimation
Amira Guesmi
Muhammad Abdullah Hanif
B. Ouni
Muhammad Shafique
MDE
32
12
0
06 Aug 2023
Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems
Runtime Stealthy Perception Attacks against DNN-based Adaptive Cruise Control Systems
Xugui Zhou
Anqi Chen
Maxfield Kouzel
Haotian Ren
Morgan McCarty
Cristina Nita-Rotaru
H. Alemzadeh
AAML
26
1
0
18 Jul 2023
Reliable learning in challenging environments
Reliable learning in challenging environments
Maria-Florina Balcan
Steve Hanneke
Rattana Pukdee
Dravyansh Sharma
OOD
30
4
0
06 Apr 2023
AdvART: Adversarial Art for Camouflaged Object Detection Attacks
AdvART: Adversarial Art for Camouflaged Object Detection Attacks
Amira Guesmi
Ioan Marius Bilasco
Muhammad Shafique
Ihsen Alouani
GAN
AAML
34
20
0
03 Mar 2023
Improving Adversarial Transferability with Scheduled Step Size and Dual
  Example
Improving Adversarial Transferability with Scheduled Step Size and Dual Example
Zeliang Zhang
Peihan Liu
Xiaosen Wang
Chenliang Xu
AAML
21
3
0
30 Jan 2023
Scoring Black-Box Models for Adversarial Robustness
Scoring Black-Box Models for Adversarial Robustness
Jian Vora
Pranay Reddy Samala
25
0
0
31 Oct 2022
Improving the Robustness of Adversarial Attacks Using an
  Affine-Invariant Gradient Estimator
Improving the Robustness of Adversarial Attacks Using an Affine-Invariant Gradient Estimator
Wenzhao Xiang
Hang Su
Chang-rui Liu
Yandong Guo
Shibao Zheng
AAML
27
5
0
13 Sep 2021
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve
  Adversarial Robustness
Learn2Perturb: an End-to-end Feature Perturbation Learning to Improve Adversarial Robustness
Ahmadreza Jeddi
M. Shafiee
Michelle Karg
C. Scharfenberger
A. Wong
OOD
AAML
50
63
0
02 Mar 2020
Analysis of Random Perturbations for Robust Convolutional Neural
  Networks
Analysis of Random Perturbations for Robust Convolutional Neural Networks
Adam Dziedzic
S. Krishnan
OOD
AAML
16
1
0
08 Feb 2020
The Threat of Adversarial Attacks on Machine Learning in Network
  Security -- A Survey
The Threat of Adversarial Attacks on Machine Learning in Network Security -- A Survey
Olakunle Ibitoye
Rana Abou-Khamis
Mohamed el Shehaby
Ashraf Matrawy
M. O. Shafiq
AAML
26
68
0
06 Nov 2019
Impact of Low-bitwidth Quantization on the Adversarial Robustness for
  Embedded Neural Networks
Impact of Low-bitwidth Quantization on the Adversarial Robustness for Embedded Neural Networks
Rémi Bernhard
Pierre-Alain Moëllic
J. Dutertre
AAML
MQ
22
18
0
27 Sep 2019
Adversarial Machine Learning at Scale
Adversarial Machine Learning at Scale
Alexey Kurakin
Ian Goodfellow
Samy Bengio
AAML
261
3,109
0
04 Nov 2016
Adversarial examples in the physical world
Adversarial examples in the physical world
Alexey Kurakin
Ian Goodfellow
Samy Bengio
SILM
AAML
281
5,835
0
08 Jul 2016
1