mlsanityData to 7 Oct 2026

Adversarial Detector with Robust Classifier

arXiv 2202.02503 ↗First posted 5 Feb 2022cs.CV cs.LGcited by 0

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Abstract (arXiv)

Deep neural network (DNN) models are wellknown to easily misclassify prediction results by using input images with small perturbations, called adversarial examples. In this paper, we propose a novel adversarial detector, which consists of a robust classifier and a plain one, to highly detect adversarial examples. The proposed adversarial detector is carried out in accordance with the logits of plain and robust classifiers. In an experiment, the proposed detector is demonstrated to outperform a state-of-the-art detector without any robust classifier.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 17 of its 20 references that are in the map. First posted on arXiv 5 Feb 2022.

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17 of 20 references.

References · 17

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2014Explaining and Harnessing Adversarial Examplescited by 7,287
  3. 2017Towards Deep Learning Models Resistant to Adversarial Attackscited by 6,326
  4. 2013Intriguing properties of neural networkscited by 5,114
  5. 2016Towards Evaluating the Robustness of Neural Networkscited by 2,976
  6. 2018A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attackscited by 1,472
  7. 2016Adversarial Machine Learning at Scalecited by 934
  8. 2017Ensemble Adversarial Training: Attacks and Defensescited by 833
  9. 2015The Limitations of Deep Learning in Adversarial Settingscited by 784
  10. 2017On Detecting Adversarial Perturbationscited by 232
  11. 2016Adversarial Examples Detection in Deep Networks with Convolutional Filter Statisticscited by 77
  12. 2019Detecting Adversarial Samples Using Influence Functions and Nearest Neighborscited by 72
5 more
  1. 2015Distributional Smoothing with Virtual Adversarial Trainingcited by 61
  2. 2019ML-LOO: Detecting Adversarial Examples with Feature Attributioncited by 48
  3. 2020Block-wise Image Transformation with Secret Key for Adversarially Robust Defensecited by 30
  4. 2022An Overview of Compressible and Learnable Image Transformation with Secret Key and Its Applicationscited by 29
  5. 2020Encryption Inspired Adversarial Defense for Visual Classificationcited by 17

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