Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Transfer Learning-Based Model Protection With Secret Key   We propose a novel method for protecting trained models with a secret key so
that unauthorized users without the correct key cannot get the correct
inference. By taking advantage of transfer learning, the proposed method
enables us to train a large protected model like a model trained with ImageNet
by using a small subset of a training dataset. It utilizes a learnable
encryption step with a secret key to generate learnable transformed images.
Models with pre-trained weights are fine-tuned by using such transformed
images. In experiments with the ImageNet dataset, it is shown that the
performance of a protected model was close to that of a non-protected model
when the correct key was given, while the accuracy tremendously dropped when an
incorrect key was used. The protected model was also demonstrated to be robust
against key estimation attacks.

23
The categories of this paper are: solv-int
28
The categories of this paper are: alg-geom
30
The categories of this paper are: q-alg
29
The categories of this paper are: funct-an
15
The categories of this paper are: nucl-ex
13
The categories of this paper are: quant-ph
20
The categories of this paper are: acc-phys
17
The categories of this paper are: q-fin
6
The categories of this paper are: astro-ph
12
The categories of this paper are: nucl-th
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
22
The categories of this paper are: chao-dyn
24
The categories of this paper are: dg-ga
34
The categories of this paper are: chem-ph
2
The categories of this paper are: math