paper-with-me

Papers

Erratum Concerning the Obfuscated Gradients Attack on Stochastic Activation Pruning

2020-09-30 · Guneet S. Dhillon, Nicholas Carlini

Stochastic Activation Pruning (SAP) (Dhillon et al., 2018) is a defense to adversarial examples that was attacked and found to be broken by the "Obfuscated Gradients" paper (Athalye et al., 2018). We discover a flaw in the re-implementation that artificially weakens SAP. When SAP is applied properly, the proposed attack is not effective. However, we show that a new use of the BPDA attack technique can still reduce the accuracy of SAP to 0.1%.

📄 PDF Abstract BibTeX arXiv:2010.00071

Code (0)

등록된 구현이 없습니다.

Methods 이 논문이 사용한 방법론

Pruning 설명 없음

Similar Papers 제목 키워드 기반

Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples

2018-02-01 · ICML 2018 7 · Anish Athalye, Nicholas Carlini, David Wagner

We identify obfuscated gradients, a kind of gradient masking, as a phenomenon that leads to a false sense of security in defenses against adversarial examples. While defenses that cause obfuscated gradients appear to def…

Adversarial AttackAdversarial Defense

Barrage of Random Transforms for Adversarially Robust Defense

2019-06-01 · CVPR 2019 6 · Edward Raff, Jared Sylvester, Steven Forsyth, Mark McLean

Defenses against adversarial examples, when using the ImageNet dataset, are historically easy to defeat. The common understanding is that a combination of simple image transformations and other various defenses are insuf…

Gradient Obfuscation Checklist Test Gives a False Sense of Security

2022-06-03 · Nikola Popovic, Danda Pani Paudel, Thomas Probst, Luc van Gool

One popular group of defense techniques against adversarial attacks is based on injecting stochastic noise into the network. The main source of robustness of such stochastic defenses however is often due to the obfuscati…

Encryption Inspired Adversarial Defense for Visual Classification

2020-05-16 · MaungMaung AprilPyone, Hitoshi Kiya

Conventional adversarial defenses reduce classification accuracy whether or not a model is under attacks. Moreover, most of image processing based defenses are defeated due to the problem of obfuscated gradients. In this…

Adversarial DefenseClassificationGeneral Classification

Imbalanced Gradients: A Subtle Cause of Overestimated Adversarial Robustness

2020-06-24 · Xingjun Ma, Linxi Jiang, Hanxun Huang, Zejia Weng 외

Evaluating the robustness of a defense model is a challenging task in adversarial robustness research. Obfuscated gradients have previously been found to exist in many defense methods and cause a false signal of robustne…

Adversarial Robustness