Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Defense against Adversarial Attacks Using High-Level Representation
  Guided Denoiser   Neural networks are vulnerable to adversarial examples, which poses a threat
to their application in security sensitive systems. We propose high-level
representation guided denoiser (HGD) as a defense for image classification.
Standard denoiser suffers from the error amplification effect, in which small
residual adversarial noise is progressively amplified and leads to wrong
classifications. HGD overcomes this problem by using a loss function defined as
the difference between the target model's outputs activated by the clean image
and denoised image. Compared with ensemble adversarial training which is the
state-of-the-art defending method on large images, HGD has three advantages.
First, with HGD as a defense, the target model is more robust to either
white-box or black-box adversarial attacks. Second, HGD can be trained on a
small subset of the images and generalizes well to other images and unseen
classes. Third, HGD can be transferred to defend models other than the one
guiding it. In NIPS competition on defense against adversarial attacks, our HGD
solution won the first place and outperformed other models by a large margin.

33
The categories of this paper are: plasm-ph
7
The categories of this paper are: hep-th
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con
24
The categories of this paper are: dg-ga
16
The categories of this paper are: stat
15
The categories of this paper are: nucl-ex
28
The categories of this paper are: alg-geom
32
The categories of this paper are: atom-ph
18
The categories of this paper are: econ
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
3
The categories of this paper are: physics
35
The categories of this paper are: mtrl-th
34
The categories of this paper are: chem-ph