Pain-FL: Personalized Privacy-Preserving Incentive for Federated Learning
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Journal on Selected Areas in Communications"
DOI: 10.1109/jsac.2021.3118354
Abstract: Federated learning (FL) is a privacy-preserving distributed machine learning framework, which involves training statistical models over a number of mobile users (i.e., workers) while keeping data localized. However, recent works have demonstrated that workers engaged… read more here.
Keywords: incentive; privacy; personalized privacy; pain ... See more keywords
Towards Personalized Privacy-Preserving Truth Discovery Over Crowdsourced Data Streams
Sign Up to like & getrecommendations! Published in 2022 at "IEEE/ACM Transactions on Networking"
DOI: 10.1109/tnet.2021.3110052
Abstract: Truth discovery is an effective paradigm which could reveal the truth from crowdsouced data with conflicts, enabling data-driven decision-making systems to make quick and smart decisions. The increasing privacy concern promotes users to perturb or… read more here.
Keywords: truth; truth discovery; personalized privacy; privacy preserving ... See more keywords
Personalized Privacy Assistant: Identity Construction and Privacy in the Internet of Things
Sign Up to like & getrecommendations! Published in 2023 at "Entropy"
DOI: 10.3390/e25050717
Abstract: Over time, the many different ways in which we collect and use data have become more complex as we communicate and interact with an ever-increasing variety of modern technologies. Although people often say they care… read more here.
Keywords: identity; privacy assistant; personalized privacy; assistant identity ... See more keywords