Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Neural Network Laundering: Removing Black-Box Backdoor Watermarks from
  Deep Neural Networks   Creating a state-of-the-art deep-learning system requires vast amounts of
data, expertise, and hardware, yet research into embedding copyright protection
for neural networks has been limited. One of the main methods for achieving
such protection involves relying on the susceptibility of neural networks to
backdoor attacks, but the robustness of these tactics has been primarily
evaluated against pruning, fine-tuning, and model inversion attacks. In this
work, we propose a neural network "laundering" algorithm to remove black-box
backdoor watermarks from neural networks even when the adversary has no prior
knowledge of the structure of the watermark.
  We are able to effectively remove watermarks used for recent defense or
copyright protection mechanisms while achieving test accuracies above 97% and
80% for both MNIST and CIFAR-10, respectively. For all backdoor watermarking
methods addressed in this paper, we find that the robustness of the watermark
is significantly weaker than the original claims. We also demonstrate the
feasibility of our algorithm in more complex tasks as well as in more realistic
scenarios where the adversary is able to carry out efficient laundering attacks
using less than 1% of the original training set size, demonstrating that
existing backdoor watermarks are not sufficient to reach their claims.

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The categories of this paper are: q-alg
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
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The categories of this paper are: atom-ph
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
21
The categories of this paper are: adap-org
2
The categories of this paper are: math
15
The categories of this paper are: nucl-ex
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The categories of this paper are: cmp-lg
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The categories of this paper are: bayes-an
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The categories of this paper are: econ
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The categories of this paper are: math-ph
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The categories of this paper are: eess
17
The categories of this paper are: q-fin