11 citations · 19 across the 3 of their papers we have counts for
3 papers
cs.CR2022★ 2 cited
Demystifying Arch-hints for Model Extraction: An Attack in Unified Memory System
Zhendong Wang, Xiaoming Zeng, Xulong Tang +3
The deep neural network (DNN) models are deemed confidential due to their unique value in expensive training efforts, privacy-sensitive training data, and proprietary network chara…
cs.LG2021★ 6 cited
DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks
Yingzhe He, Guozhu Meng, Kai Chen +2
Machine unlearning has great significance in guaranteeing model security and protecting user privacy. Additionally, many legal provisions clearly stipulate that users have the righ…
cs.CR2019★ 11 cited
Towards Security Threats of Deep Learning Systems: A Survey
Yingzhe He, Guozhu Meng, Kai Chen +2
Deep learning has gained tremendous success and great popularity in the past few years. However, deep learning systems are suffering several inherent weaknesses, which can threaten…