Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning
X Yang, O Ardakanian - ACM Transactions on Sensor Networks, 2023 - dl.acm.org
This article proposes a sensor data anonymization model that is trained on decentralized
data and strikes a desirable trade-off between data utility and privacy, even in …
data and strikes a desirable trade-off between data utility and privacy, even in …
[PDF][PDF] Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning
XIN YANG, O ARDAKANIAN - 2023 - neilyxin.com
Networked, embedded sensors are prevalent in today's urban infrastructure and mobile
devices. The vast amount of data emitted by them and the increasing ability to train machine …
devices. The vast amount of data emitted by them and the increasing ability to train machine …
Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning
X Yang, O Ardakanian - arXiv preprint arXiv:2209.12046, 2022 - arxiv.org
This paper proposes a sensor data anonymization model that is trained on decentralized
data and strikes a desirable trade-off between data utility and privacy, even in …
data and strikes a desirable trade-off between data utility and privacy, even in …
Blinder: End-to-end Privacy Protection in Sensing Systems via Personalized Federated Learning
X Yang, O Ardakanian - arXiv e-prints, 2022 - ui.adsabs.harvard.edu
This paper proposes a sensor data anonymization model that is trained on decentralized
data and strikes a desirable trade-off between data utility and privacy, even in …
data and strikes a desirable trade-off between data utility and privacy, even in …