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Adversarial Attack Detection

The detection of adversarial attacks.

Papers

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Showing 1–25 of 38 papers

TitleStatusHype
Maximum Mean Discrepancy Test is Aware of Adversarial AttacksCode1
Towards Feature Space Adversarial AttackCode1
Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch DetectionCode1
OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated ExamplesCode1
Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?Code1
Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural NetworksCode0
Graph-based methods coupled with specific distributional distances for adversarial attack detectionCode0
Neural Fingerprints for Adversarial Attack DetectionCode0
Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view InconsistencyCode0
Uncertainty Estimation of Transformer Predictions for Misclassification DetectionCode0
Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial DetectionCode0
A Few Large Shifts: Layer-Inconsistency Based Minimal Overhead Adversarial Example DetectionCode0
Detecting Adversarial Examples in Batches -- a geometrical approachCode0
Residue-Based Natural Language Adversarial Attack DetectionCode0
MetaAdvDet: Towards Robust Detection of Evolving Adversarial AttacksCode0
Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial RobustnessCode0
Residue-Based Natural Language Adversarial Attack Detection—0
Resilient and constrained consensus against adversarial attacks: A distributed MPC framework—0
Robust Adversarial Attacks Detection for Deep Learning based Relative Pose Estimation for Space Rendezvous—0
Self-Supervised Representation Learning for Adversarial Attack Detection—0
Learning to Attack with Fewer Pixels: A Probabilistic Post-hoc Framework for Refining Arbitrary Dense Adversarial Attacks—0
Unleashing the Power of Pre-trained Encoders for Universal Adversarial Attack Detection—0
Using Anomaly Feature Vectors for Detecting, Classifying and Warning of Outlier Adversarial Examples—0
ASVspoof 5: Design, Collection and Validation of Resources for Spoofing, Deepfake, and Adversarial Attack Detection Using Crowdsourced Speech—0
Attack-Agnostic Adversarial Detection—0
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