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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 1241–1250 of 1808 papers

Title	Date	Tasks	Status	Hype	Score
PhantomSound: Black-Box, Query-Efficient Audio Adversarial Attack via Split-Second Phoneme Injection	Sep 13, 2023	Adversarial AttackSpeech-to-Text	—Unverified	0	0
Phrase-level Textual Adversarial Attack with Label Preservation	Jan 16, 2022	Adversarial AttackSentence	—Unverified	0	0
Adversarial Identity Injection for Semantic Face Image Synthesis	Apr 16, 2024	Adversarial AttackFace Generation	—Unverified	0	0
Adversarial Fine-tune with Dynamically Regulated Adversary	Apr 28, 2022	Adversarial AttackAdversarial Robustness	—Unverified	0	0
Adversarial Exposure Attack on Diabetic Retinopathy Imagery Grading	Sep 19, 2020	Adversarial Attack	—Unverified	0	0
Physical Adversarial Attack on Monocular Depth Estimation via Shape-Varying Patches	Jul 24, 2024	Adversarial AttackAutonomous Driving	—Unverified	0	0
Physical Adversarial Attack on Vehicle Detector in the Carla Simulator	Jul 31, 2020	Adversarial Attack	—Unverified	0	0
Physical Adversarial Attacks For Camera-based Smart Systems: Current Trends, Categorization, Applications, Research Challenges, and Future Outlook	Aug 11, 2023	Adversarial AttackDepth Estimation	—Unverified	0	0
Adversarial Examples in Deep Learning: Characterization and Divergence	Jun 29, 2018	Adversarial AttackDeep Learning	—Unverified	0	0
PICA: A Pixel Correlation-based Attentional Black-box Adversarial Attack	Jan 19, 2021	Adversarial Attack	—Unverified	0	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