TY - GEN
T1 - Collaborative Mean Estimation over Intermittently Connected Networks with Peer-To-Peer Privacy
AU - Saha, Rajarshi
AU - Seif, Mohamed
AU - Yemini, Michal
AU - Goldsmith, Andrea J.
AU - Vincent Poor, H.
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This work considers the problem of Distributed Mean Estimation (DME) over networks with intermittent connectivity, where the goal is to learn a global statistic over the data samples localized across distributed nodes with the help of a central server. To mitigate the impact of intermittent links, nodes can collaborate with their neighbors to compute local consensus which they forward to the central server. In such a setup, the communications between any pair of nodes must satisfy local differential privacy constraints. We study the tradeoff between collaborative relaying and privacy leakage due to the additional data sharing among nodes and, subsequently, propose a novel differentially private collaborative algorithm for DME to achieve the optimal tradeoff. Finally, we present numerical simulations to substantiate our theoretical findings.
AB - This work considers the problem of Distributed Mean Estimation (DME) over networks with intermittent connectivity, where the goal is to learn a global statistic over the data samples localized across distributed nodes with the help of a central server. To mitigate the impact of intermittent links, nodes can collaborate with their neighbors to compute local consensus which they forward to the central server. In such a setup, the communications between any pair of nodes must satisfy local differential privacy constraints. We study the tradeoff between collaborative relaying and privacy leakage due to the additional data sharing among nodes and, subsequently, propose a novel differentially private collaborative algorithm for DME to achieve the optimal tradeoff. Finally, we present numerical simulations to substantiate our theoretical findings.
UR - http://www.scopus.com/inward/record.url?scp=85171440493&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85171440493&partnerID=8YFLogxK
U2 - 10.1109/ISIT54713.2023.10206910
DO - 10.1109/ISIT54713.2023.10206910
M3 - Conference contribution
AN - SCOPUS:85171440493
T3 - IEEE International Symposium on Information Theory - Proceedings
SP - 174
EP - 179
BT - 2023 IEEE International Symposium on Information Theory, ISIT 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 IEEE International Symposium on Information Theory, ISIT 2023
Y2 - 25 June 2023 through 30 June 2023
ER -