3 citations · 3 across the 2 of their papers we have counts for
5 papers
Attacks to Federated Learning: Responsive Web User Interface to Recover Training Data from User Gradients
Hans Albert Lianto, Yang Zhao, Jun Zhao
Local differential privacy (LDP) is an emerging privacy standard to protect individual user data. One scenario where LDP can be applied is federated learning, where each user sends…
Blockchain-Based Differential Privacy Cost Management System
Leong Mei Han, Yang Zhao, Jun Zhao
Privacy preservation is a big concern for various sectors. To protect individual user data, one emerging technology is differential privacy. However, it still has limitations for d…
Local Differential Privacy based Federated Learning for Internet of Things
Yang Zhao, Jun Zhao, Mengmeng Yang +5
Internet of Vehicles (IoV) is a promising branch of the Internet of Things. IoV simulates a large variety of crowdsourcing applications such as Waze, Uber, and Amazon Mechanical Tu…
A Blockchain-Based Approach for Saving and Tracking Differential-Privacy Cost
Yang Zhao, Jun Zhao, Jiawen Kang +3
An increasing amount of users' sensitive information is now being collected for analytics purposes. To protect users' privacy, differential privacy has been widely studied in the l…
Privacy-Preserving Blockchain-Based Federated Learning for IoT Devices
Yang Zhao, Jun Zhao, Linshan Jiang +5
Home appliance manufacturers strive to obtain feedback from users to improve their products and services to build a smart home system. To help manufacturers develop a smart home sy…