3 citations · 3 across the 2 of their papers we have counts for
3 papers
cs.CR2022★ 3 cited
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations
Zirui Peng, Shaofeng Li, Guoxing Chen +3
In this paper, we propose a novel and practical mechanism which enables the service provider to verify whether a suspect model is stolen from the victim model via model extraction…
cs.CV2021
Countering Adversarial Examples: Combining Input Transformation and Noisy Training
Cheng Zhang, Pan Gao
Recent studies have shown that neural network (NN) based image classifiers are highly vulnerable to adversarial examples, which poses a threat to security-sensitive image recogniti…
cs.CR2020
Progressive Defense Against Adversarial Attacks for Deep Learning as a Service in Internet of Things
Ling Wang, Cheng Zhang, Zejian Luo +4
Nowadays, Deep Learning as a service can be deployed in Internet of Things (IoT) to provide smart services and sensor data processing. However, recent research has revealed that so…