FedMEC: Improving Efficiency of Differentially Private Federated Learning via Mobile Edge Computing
Sign Up to like & getrecommendations! Published in 2020 at "Mobile Networks and Applications"
DOI: 10.1007/s11036-020-01586-4
Abstract: Federated learning is a recently proposed paradigm that presents significant advantages in privacy-preserving machine learning services. It enables the deep learning applications on mobile devices, where a deep neural network (DNN) is trained in a… read more here.
Keywords: federated learning; edge computing; differentially private; edge ... See more keywords
Cloud-based differentially private image classification
Sign Up to like & getrecommendations! Published in 2018 at "Wireless Networks"
DOI: 10.1007/s11276-018-1885-y
Abstract: AbstractIn this paper, our aim is to design and develop an anonymous full-duplex image classification framework under Differential Privacy. We work under the assumption that both, the cloud and the querier are semi-trusted entities, thus… read more here.
Keywords: image; classification; differentially private; image classification ... See more keywords
Utility-efficient Differentially Private K-means Clustering based on Cluster Merging
Sign Up to like & getrecommendations! Published in 2021 at "Neurocomputing"
DOI: 10.1016/j.neucom.2020.10.051
Abstract: Differential privacy is widely used in data analysis. State-of-the-art $k$-means clustering algorithms with differential privacy typically add an equal amount of noise to centroids for each iterative computation. In this paper, we propose a novel… read more here.
Keywords: differential privacy; utility; means clustering; differentially private ... See more keywords
An Optimizing and Differentially Private Clustering Algorithm for Mixed Data in SDN-Based Smart Grid
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2909048
Abstract: Software-defined network (SDN) is widely used in smart grid for monitoring and managing the communication network. Big data analytics for SDN-based smart grid has got increasing attention. It is a promising approach to use machine… read more here.
Keywords: based smart; smart grid; differentially private; privacy ... See more keywords
DPARM: Differentially Private Association Rules Mining
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3013157
Abstract: Association analysis is critical in data analysis performed to find all co-occurrence relationships ( $i.e$ ., frequent itemsets or confident association rules) from the transactional dataset. An association rule can improve the ability of users… read more here.
Keywords: association rules; differentially private; association; private association ... See more keywords
Designing Contracts for Trading Private and Heterogeneous Data Using a Biased Differentially Private Algorithm
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3074478
Abstract: Personal information and other types of private data are valuable for both data owners and institutions interested in providing targeted and customized services that require analyzing such data. In this context, privacy is sometimes seen… read more here.
Keywords: designing contracts; private data; contracts trading; using biased ... See more keywords
Differentially Private High-Dimensional Data Publication in Internet of Things
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2019.2955503
Abstract: Internet of Things and the related computing paradigms, such as cloud computing and fog computing, provide solutions for various applications and services with massive and high-dimensional data, while producing threats to the personal privacy. Differential… read more here.
Keywords: dimensional data; internet things; high dimensional; privacy ... See more keywords
Incentivizing Differentially Private Federated Learning: A Multidimensional Contract Approach
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3050163
Abstract: Federated learning is a promising tool in the Internet-of-Things (IoT) domain for training a machine learning model in a decentralized manner. Specifically, the data owners (e.g., IoT device consumers) keep their raw data and only… read more here.
Keywords: private federated; federated learning; model; incentive mechanism ... See more keywords
Privately Publishing Internet of Things Data: Bring Personalized Sampling Into Differentially Private Mechanisms
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2021.3089518
Abstract: Massive Internet of Things (IoT) data sets are possessed by big institutions serving daily life because IoT devices are widely used in our daily life such as wearable devices and smart home devices. Publishing these… read more here.
Keywords: personalized sampling; private mechanisms; internet things; data sets ... See more keywords
Differentially Private Federated Learning via Reconfigurable Intelligent Surface
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3168066
Abstract: Federated learning (FL), as a disruptive machine learning (ML) paradigm, enables the collaborative training of a global model over decentralized local data sets without sharing them. It spans a wide scope of applications from the… read more here.
Keywords: intelligent surface; federated learning; differentially private; private federated ... See more keywords
Differentially Private Crowdsourcing With the Public and Private Blockchain
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Internet of Things Journal"
DOI: 10.1109/jiot.2022.3233360
Abstract: As a result of the rapid development of Internet of Things (IoT) systems, an increasing number of academics are focusing on finding new applications for IoT systems. For IoT systems, crowdsourcing is a prevalent practise.… read more here.
Keywords: blockchain; public private; differentially private; iot systems ... See more keywords