Adversarial Attack Detection

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16 shown of 16 papers with code (38 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• Is RobustBench/AutoAttack a suitable Benchmark for Adversarial Robustness?
  2 Dec 2021 2 repositories listed
  In its most commonly reported sub-task, RobustBench evaluates and ranks the adversarial robustness of trained neural networks on CIFAR10 under AutoAttack (Croce and Hein 2020b) with l-inf perturbations limited to eps =…
• Maximum Mean Discrepancy Test is Aware of Adversarial Attacks
  22 Oct 2020 2 repositories listed
  However, it has been shown that the MMD test is unaware of adversarial attacks -- the MMD test failed to detect the discrepancy between natural and adversarial data.
• A Few Large Shifts: Layer-Inconsistency Based Minimal Overhead Adversarial Example Detection
  19 May 2025 1 repository listed
  Deep neural networks (DNNs) are highly susceptible to adversarial examples--subtle, imperceptible perturbations that can lead to incorrect predictions.
• Neural Fingerprints for Adversarial Attack Detection
  7 Nov 2024 1 repository listed
  Despite the good performance of these detectors, we argue that in a white-box setting, where the attacker knows the configuration and weights of the network and the detector, they can overcome the detector by running…
• OUTFOX: LLM-Generated Essay Detection Through In-Context Learning with Adversarially Generated Examples
  21 Jul 2023 1 repository listed Syntology ran 6 of 8 samples · 2 unverified
  Experiments in the domain of student essays show that the proposed detector improves the detection performance on the attacker-generated texts by up to +41.
• Graph-based methods coupled with specific distributional distances for adversarial attack detection
  31 May 2023 1 repository listed
  We introduce a novel approach of detection and interpretation of adversarial attacks from a graph perspective.
• Unfolding Local Growth Rate Estimates for (Almost) Perfect Adversarial Detection
  13 Dec 2022 1 repository listed
  Convolutional neural networks (CNN) define the state-of-the-art solution on many perceptual tasks.
• Detecting Adversarial Examples in Batches -- a geometrical approach
  17 Jun 2022 1 repository listed
  Many deep learning methods have successfully solved complex tasks in computer vision and speech recognition applications.
• Uncertainty Estimation of Transformer Predictions for Misclassification Detection
  1 May 2022 1 repository listed
  Uncertainty estimation (UE) of model predictions is a crucial step for a variety of tasks such as active learning, misclassification detection, adversarial attack detection, out-of-distribution detection, etc.
• Residue-Based Natural Language Adversarial Attack Detection
  17 Apr 2022 1 repository listed
  Many popular image adversarial detection approaches are able to identify adversarial examples from embedding feature spaces, whilst in the NLP domain existing state of the art detection approaches solely focus on input…
• Segment and Complete: Defending Object Detectors against Adversarial Patch Attacks with Robust Patch Detection
  8 Dec 2021 1 repository listed Syntology ran 3 of 3 samples · 0 unverified · 3 pointer-only (licence)
  In addition, we design a robust shape completion algorithm, which is guaranteed to remove the entire patch from the images if the outputs of the patch segmenter are within a certain Hamming distance of the ground-truth…
• Two Souls in an Adversarial Image: Towards Universal Adversarial Example Detection using Multi-view Inconsistency
  25 Sep 2021 1 repository listed
  To this end, Argos first amplifies the discrepancies between the visual content of an image and its misclassified label induced by the attack using a set of regeneration mechanisms and then identifies an image as…
• Towards Feature Space Adversarial Attack
  26 Apr 2020 1 repository listed
  We propose a new adversarial attack to Deep Neural Networks for image classification.
• MetaAdvDet: Towards Robust Detection of Evolving Adversarial Attacks
  6 Aug 2019 1 repository listed
  To solve such few-shot problem with the evolving attack, we propose a meta-learning based robust detection method to detect new adversarial attacks with limited examples.
• Reverse KL-Divergence Training of Prior Networks: Improved Uncertainty and Adversarial Robustness
  31 May 2019 1 repository listed
  Second, taking advantage of this new training criterion, this paper investigates using Prior Networks to detect adversarial attacks and proposes a generalized form of adversarial training.
• Gotta Catch 'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks
  18 Apr 2019 1 repository listed
  Attackers' optimization algorithms gravitate towards trapdoors, leading them to produce attacks similar to trapdoors in the feature space.

Syntology lines on 2 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.