Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Using a GAN to Generate Adversarial Examples to Facial Image Recognition   Images posted online present a privacy concern in that they may be used as
reference examples for a facial recognition system. Such abuse of images is in
violation of privacy rights but is difficult to counter. It is well established
that adversarial example images can be created for recognition systems which
are based on deep neural networks. These adversarial examples can be used to
disrupt the utility of the images as reference examples or training data. In
this work we use a Generative Adversarial Network (GAN) to create adversarial
examples to deceive facial recognition and we achieve an acceptable success
rate in fooling the face recognition. Our results reduce the training time for
the GAN by removing the discriminator component. Furthermore, our results show
knowledge distillation can be employed to drastically reduce the size of the
resulting model without impacting performance indicating that our contribution
could run comfortably on a smartphone

37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
2
The categories of this paper are: math
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
36
The categories of this paper are: cmp-lg