New directions in IoT privacy using attribute-based authentication
The Internet of Things (IoT) is a ubiquitous system that incorporates not only the current
Internet of computers, but also smart objects and sensors. IoT technologies often rely on …
Internet of computers, but also smart objects and sensors. IoT technologies often rely on …
Differentially Private Federated Tensor Completion for Cloud-Edge Collaborative AIoT Data Prediction
Artificial Intelligence of Things (AIoT) is an emerging paradigm that integrates artificial
intelligence (AI) and Internet of Things (IoT) technologies to provide intelligent IoT solutions …
intelligence (AI) and Internet of Things (IoT) technologies to provide intelligent IoT solutions …
Privacy preserving data aggregation scheme for mobile edge computing assisted IoT applications
As the rapid development of 5G and Internet of Things (IoT) techniques, more and more
mobile devices with specific sensing capabilities access to the network and large amounts of …
mobile devices with specific sensing capabilities access to the network and large amounts of …
PDLM: Privacy-preserving deep learning model on cloud with multiple keys
Deep learning has aroused a lot of attention and has been used successfully in many
domains, such as accurate image recognition and medical diagnosis. Generally, the training …
domains, such as accurate image recognition and medical diagnosis. Generally, the training …
A numerical splitting and adaptive privacy budget-allocation-based LDP mechanism for privacy preservation in blockchain-powered IoT
Blockchain has gradually attracted widespread attention from the research community of the
IoT, due to its decentralization, consistency, and other attributes. It builds a secure and …
IoT, due to its decentralization, consistency, and other attributes. It builds a secure and …
[PDF][PDF] Mobile edge computing, blockchain and reputation-based crowdsourcing IoT federated learning: A secure, decentralized and privacy-preserving system
Internet-of-Things (IoT) companies strive to get feedback from users to improve their
products and services. However, traditional surveys cannot reflect the actual conditions of …
products and services. However, traditional surveys cannot reflect the actual conditions of …
CrowdFL: Privacy-Preserving Mobile Crowdsensing System Via Federated Learning
As an emerging sensing data collection paradigm, mobile crowdsensing (MCS) enjoys good
scalability and low deployment cost but raises privacy concerns. In this paper, we propose a …
scalability and low deployment cost but raises privacy concerns. In this paper, we propose a …
A differential approach for data and classification service-based privacy-preserving machine learning model in cloud environment
The massive upsurge in computational and storage has driven the local data and machine
learning applications to the cloud environment. The owners may not fully trust the cloud …
learning applications to the cloud environment. The owners may not fully trust the cloud …
Blockchain and federated edge learning for privacy-preserving mobile crowdsensing
Mobile crowdsensing (MCS) counting on the mobility of massive workers helps the
requestor accomplish various sensing tasks with more flexibility and lower cost. However, for …
requestor accomplish various sensing tasks with more flexibility and lower cost. However, for …
Privacy protection federated learning system based on blockchain and edge computing in mobile crowdsourcing
W Wang, Y Wang, Y Huang, C Mu, Z Sun, X Tong… - Computer Networks, 2022 - Elsevier
With the rapid popularization and development of the Internet of Things (IoT) and 5G
networks, mobile crowdsourcing (MCS) has become an indispensable part in today's …
networks, mobile crowdsourcing (MCS) has become an indispensable part in today's …