Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Weakening the Detecting Capability of CNN-based Steganalysis   Recently, the application of deep learning in steganalysis has drawn many
researchers' attention. Most of the proposed steganalytic deep learning models
are derived from neural networks applied in computer vision. These kinds of
neural networks have distinguished performance. However, all these kinds of
back-propagation based neural networks may be cheated by forging input named
the adversarial example. In this paper we propose a method to generate
steganographic adversarial example in order to enhance the steganographic
security of existing algorithms. These adversarial examples can increase the
detection error of steganalytic CNN. The experiments prove the effectiveness of
the proposed method.

29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
15
The categories of this paper are: nucl-ex
12
The categories of this paper are: nucl-th
27
The categories of this paper are: comp-gas
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
17
The categories of this paper are: q-fin
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
24
The categories of this paper are: dg-ga