Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Integrity Fingerprinting of DNN with Double Black-box Design and
  Verification   Cloud-enabled Machine Learning as a Service (MLaaS) has shown enormous
promise to transform how deep learning models are developed and deployed.
Nonetheless, there is a potential risk associated with the use of such services
since a malicious party can modify them to achieve an adverse result.
Therefore, it is imperative for model owners, service providers, and end-users
to verify whether the deployed model has not been tampered with or not. Such
verification requires public verifiability (i.e., fingerprinting patterns are
available to all parties, including adversaries) and black-box access to the
deployed model via APIs. Existing watermarking and fingerprinting approaches,
however, require white-box knowledge (such as gradient) to design the
fingerprinting and only support private verifiability, i.e., verification by an
honest party.
  In this paper, we describe a practical watermarking technique that enables
black-box knowledge in fingerprint design and black-box queries during
verification. The service ensures the integrity of cloud-based services through
public verification (i.e. fingerprinting patterns are available to all parties,
including adversaries). If an adversary manipulates a model, this will result
in a shift in the decision boundary. Thus, the underlying principle of
double-black watermarking is that a model's decision boundary could serve as an
inherent fingerprint for watermarking. Our approach captures the decision
boundary by generating a limited number of encysted sample fingerprints, which
are a set of naturally transformed and augmented inputs enclosed around the
model's decision boundary in order to capture the inherent fingerprints of the
model. We evaluated our watermarking approach against a variety of model
integrity attacks and model compression attacks.

3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
4
The categories of this paper are: cond-mat
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
22
The categories of this paper are: chao-dyn
34
The categories of this paper are: chem-ph
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
19
The categories of this paper are: eess
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex