Adversarial Attack

An Adversarial Attack is a technique to find a perturbation that changes the prediction of a machine learning model. The perturbation can be very small and imperceptible to human eyes.

Source: Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 226–250 of 1808 papers

Title	Date	Tasks	Status	Hype
Online Adversarial Attacks	Mar 2, 2021	Adversarial Attack	CodeCode Available	1
Targeted Attack against Deep Neural Networks via Flipping Limited Weight Bits	Feb 21, 2021	Adversarial AttackBackdoor Attack	CodeCode Available	1
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning	Feb 20, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Robust Reinforcement Learning on State Observations with Learned Optimal Adversary	Jan 21, 2021	Adversarial Attackcontinuous-control	CodeCode Available	1
Robustness of on-device Models: Adversarial Attack to Deep Learning Models on Android Apps	Jan 12, 2021	Adversarial AttackDeep Learning	CodeCode Available	1
Patch-wise++ Perturbation for Adversarial Targeted Attacks	Dec 31, 2020	Adversarial Attack	CodeCode Available	1
Sparse Adversarial Attack to Object Detection	Dec 26, 2020	Adversarial AttackObject	CodeCode Available	1
Deep Feature Space Trojan Attack of Neural Networks by Controlled Detoxification	Dec 21, 2020	Adversarial AttackBackdoor Attack	CodeCode Available	1
Efficient Training of Robust Decision Trees Against Adversarial Examples	Dec 18, 2020	Adversarial Attack	CodeCode Available	1
Disentangled Information Bottleneck	Dec 14, 2020	Adversarial AttackOut-of-Distribution Detection	CodeCode Available	1
SPAA: Stealthy Projector-based Adversarial Attacks on Deep Image Classifiers	Dec 10, 2020	Adversarial Attack	CodeCode Available	1
Composite Adversarial Attacks	Dec 10, 2020	Adversarial AttackAdversarial Robustness	CodeCode Available	1
Geometric Adversarial Attacks and Defenses on 3D Point Clouds	Dec 10, 2020	Adversarial AttackAdversarial Defense	CodeCode Available	1
Using Feature Alignment Can Improve Clean Average Precision and Adversarial Robustness in Object Detection	Dec 8, 2020	2D Object DetectionAdversarial Attack	CodeCode Available	1
Adversarial Learning for Robust Deep Clustering	Dec 1, 2020	Adversarial AttackClustering	CodeCode Available	1
Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses	Nov 30, 2020	Adversarial AttackAdversarial Defense	CodeCode Available	1
SurFree: a fast surrogate-free black-box attack	Nov 25, 2020	Adversarial Attack	CodeCode Available	1
Augmented Lagrangian Adversarial Attacks	Nov 24, 2020	Adversarial AttackComputational Efficiency	CodeCode Available	1
FoolHD: Fooling speaker identification by Highly imperceptible adversarial Disturbances	Nov 17, 2020	Adversarial AttackSpeaker Identification	CodeCode Available	1
Combining GANs and AutoEncoders for Efficient Anomaly Detection	Nov 16, 2020	Adversarial AttackAnomaly Detection	CodeCode Available	1
Single-Node Attacks for Fooling Graph Neural Networks	Nov 6, 2020	Adversarial Attack	CodeCode Available	1
Perception Matters: Exploring Imperceptible and Transferable Anti-forensics for GAN-generated Fake Face Imagery Detection	Oct 29, 2020	Adversarial AttackFace Detection	CodeCode Available	1
Object Hider: Adversarial Patch Attack Against Object Detectors	Oct 28, 2020	Adversarial AttackObject	CodeCode Available	1
GreedyFool: Distortion-Aware Sparse Adversarial Attack	Oct 26, 2020	Adversarial Attack	CodeCode Available	1
Maximum Mean Discrepancy Test is Aware of Adversarial Attacks	Oct 22, 2020	Adversarial AttackAdversarial Attack Detection	CodeCode Available	1

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All datasets CIFAR-10 CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	Xu et al.	Attack: PGD20	78.68	—	Unverified
2	3-ensemble of multi-resolution self-ensembles	Attack: AutoAttack	78.13	—	Unverified
3	TRADES-ANCRA/ResNet18	Attack: AutoAttack	59.7	—	Unverified
4	AdvTraining [madry2018]	Attack: PGD20	48.44	—	Unverified
5	TRADES [zhang2019b]	Attack: PGD20	45.9	—	Unverified
6	XU-Net	Robust Accuracy	1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	3-ensemble of multi-resolution self-ensembles	Attack: AutoAttack	51.28	—	Unverified
2	multi-resolution self-ensembles	Attack: AutoAttack	47.85	—	Unverified