1.2k citations · 1.3k across the 12 of their papers we have counts for
8 papers · 1 filter
STR: Secure Computation on Additive Shares Using the Share-Transform-Reveal Strategy
Zhihua Xia, Qi Gu, Wenhao Zhou +3
The rapid development of cloud computing has probably benefited each of us. However, the privacy risks brought by untrustworthy cloud servers arise the attention of more and more p…
Privacy-Preserving Image Retrieval Based on Additive Secret Sharing
Zhihua Xia, Qi Gu, Lizhi Xiong +2
The rapid growth of digital images motivates individuals and organizations to upload their images to the cloud server. To preserve privacy, image owners would prefer to encrypt the…
Efficient Privacy-Preserving Computation Based on Additive Secret Sharing
Lizhi Xiong, Wenhao Zhou, Zhihua Xia +2
The emergence of cloud computing provides a new computing paradigm for users -- massive and complex computing tasks can be outsourced to cloud servers. However, the privacy issues…
RDP-GAN: A Rényi-Differential Privacy based Generative Adversarial Network
Chuan Ma, Jun Li, Ming Ding +4
Generative adversarial network (GAN) has attracted increasing attention recently owing to its impressive ability to generate realistic samples with high privacy protection. Without…
MSPPIR: Multi-source privacy-preserving image retrieval in cloud computing
Qi Gu, Zhihua Xia, Xingming Sun
Content-Based Image Retrieval (CBIR) techniques have been widely researched and in service with the help of cloud computing like Google Images. However, the images always contain r…
Privacy-preserving Medical Treatment System through Nondeterministic Finite Automata
Yang Yang, Robert H. Deng, Ximeng Liu +4
In this paper, we propose a privacy-preserving medical treatment system using nondeterministic finite automata (NFA), hereafter referred to as P-Med, designed for the remote medica…
DAMIA: Leveraging Domain Adaptation as a Defense against Membership Inference Attacks
Hongwei Huang, Weiqi Luo, Guoqiang Zeng +3
Deep Learning (DL) techniques allow ones to train models from a dataset to solve tasks. DL has attracted much interest given its fancy performance and potential market value, while…
SecEL: Privacy-Preserving, Verifiable and Fault-Tolerant Edge Learning for Autonomous Vehicles
Jiasi Weng, Jian Weng, Yue Zhang +2
Mobile edge computing (MEC) is an emerging technology to transform the cloud-based computing services into the edge-based ones. Autonomous vehicular network (AVNET), as one of the…