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 1526–1550 of 1808 papers

Title	Date	Tasks	Status	Hype
Square Attack: a query-efficient black-box adversarial attack via random search	Nov 29, 2019	Adversarial Attack	CodeCode Available	1
Towards Security Threats of Deep Learning Systems: A Survey	Nov 28, 2019	Adversarial AttackDeep Learning	—Unverified	0
Light-weight Calibrator: a Separable Component for Unsupervised Domain Adaptation	Nov 28, 2019	Adversarial AttackDomain Adaptation	CodeCode Available	0
Adversarial Attack with Pattern Replacement	Nov 25, 2019	Adversarial Attack	—Unverified	0
ColorFool: Semantic Adversarial Colorization	Nov 25, 2019	Adversarial AttackColorization	CodeCode Available	0
Time-aware Gradient Attack on Dynamic Network Link Prediction	Nov 24, 2019	Adversarial AttackLink Prediction	—Unverified	0
Enhancing Cross-task Black-Box Transferability of Adversarial Examples with Dispersion Reduction	Nov 22, 2019	Adversarial Attackimage-classification	CodeCode Available	0
Controversial stimuli: pitting neural networks against each other as models of human recognition	Nov 21, 2019	Adversarial Attack	CodeCode Available	0
Heuristic Black-box Adversarial Attacks on Video Recognition Models	Nov 21, 2019	Adversarial AttackVideo Recognition	CodeCode Available	0
A New Ensemble Adversarial Attack Powered by Long-term Gradient Memories	Nov 18, 2019	Adversarial Attack	CodeCode Available	0
Black-Box Adversarial Attack with Transferable Model-based Embedding	Nov 17, 2019	Adversarial Attack	CodeCode Available	0
SMART: Skeletal Motion Action Recognition aTtack	Nov 16, 2019	Action RecognitionAdversarial Attack	—Unverified	0
Suspicion-Free Adversarial Attacks on Clustering Algorithms	Nov 16, 2019	Adversarial AttackClustering	—Unverified	0
Adversarial Embedding: A robust and elusive Steganography and Watermarking technique	Nov 14, 2019	Adversarial Attackimage-classification	—Unverified	0
Adversarial Examples in Modern Machine Learning: A Review	Nov 13, 2019	Adversarial AttackBIG-bench Machine Learning	CodeCode Available	0
Improving Robustness of Task Oriented Dialog Systems	Nov 12, 2019	Adversarial AttackData Augmentation	—Unverified	0
Few-Features Attack to Fool Machine Learning Models through Mask-Based GAN	Nov 12, 2019	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
Minimalistic Attacks: How Little it Takes to Fool a Deep Reinforcement Learning Policy	Nov 10, 2019	Adversarial AttackAtari Games	—Unverified	0
Patch augmentation: Towards efficient decision boundaries for neural networks	Nov 8, 2019	Adversarial Attack	CodeCode Available	0
Adversarial Attacks on Time-Series Intrusion Detection for Industrial Control Systems	Nov 8, 2019	Adversarial AttackIntrusion Detection	—Unverified	0
White-Box Target Attack for EEG-Based BCI Regression Problems	Nov 7, 2019	Adversarial AttackBIG-bench Machine Learning	—Unverified	0
Reversible Adversarial Attack based on Reversible Image Transformation	Nov 6, 2019	Adversarial AttackImage Restoration	—Unverified	0
Who is Real Bob? Adversarial Attacks on Speaker Recognition Systems	Nov 3, 2019	Adversarial AttackSpeaker Recognition	CodeCode Available	0
The FEVER2.0 Shared Task	Nov 1, 2019	Adversarial Attack	—Unverified	0
Adversarial Music: Real World Audio Adversary Against Wake-word Detection System	Oct 31, 2019	Adversarial AttackReal-World Adversarial Attack	—Unverified	0

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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