.png){kind=icon}
返回
Private Weighted Sum Aggregation
.png){kind=icon}
OA
AI
DOI：10.1109/TCNS.2021.3094788.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
As large amounts of data are circulated both from users to a cloud server and between users, privately aggregating the shared data is critical. This article considers the problem of private weighted sum aggregation with secret weights, where an aggregator wants to compute the weighted sum of the local data of some agents. Based on the privacy requirements posed on the weights, there are different secure multiparty computation schemes exploiting the knowledge structure. First, we review schemes for when each agent has a local private value and local private weight, and when agents have a local private value, but the aggregator holds the corresponding weights. Our main focus is the more general case, where the weights are known neither by the agents nor by the aggregator-they are generated and kept private by a system operator, and the aggregator has to compute the weighted sum without learning the agents' data or the weights. We give solutions that achieve aggregator obliviousness and design more efficient communication and computation strategies for multidimensional data by batching the data into fewer cipher-texts. Finally, we implement our schemes and discuss the numerical results.
Keyword:
Cryptography
data privacy
distributed systems
security
期刊
IF:
5
论文数:
1.7K
被引数:
5.8K
机构
引用论文
Investigation of some thermal parameters of ferrofluids in the presence of a static magnetic field
PREAI
分享收藏Interaction of .theta.-Toxin (Perfringolysin O), a Cholesterol-Binding Cytolysin, with Liposomal Membranes: Change in the Aromatic Side Chains upon Binding and Insertion.png)
Biochemistry
BiochemistryIF0
PREAI
分享收藏
查看更多内容