12 citations · 33 across the 12 of their papers we have counts for
13 papers
Secure Aggregation with Top-K Sparsification in Decentralized Federated Learning
Hengxuan Tang, Jinbao Zhu, Xiaohu Tang
Secure aggregation is a vital component for mitigating gradient leakage in federated learning, but its communication cost conventionally scales with the gradient dimension. This be…
The Capacity of Information-Theoretic Secure Aggregation in Federated Learning
Lanxin Yi, Jinbao Zhu, Kai Wan +1
Secure aggregation allows a server to aggregate users' local updates while preserving update privacy. Existing information-theoretic problems typically assume that correlated rando…
A General Coding Framework for Adaptive Private Information Retrieval
Jinbao Zhu, Xiaohu Tang
The problem of -colluding private information retrieval (PIR) enables the user to retrieve one out of files from a distributed storage system with servers without reveal…
Private Multiple Linear Computation: A Flexible Communication-Computation Tradeoff
Jinbao Zhu, Lanping Li, Xiaohu Tang +1
We consider the problem of private multiple linear computation (PMLC) over a replicated storage system with colluding and unresponsive constraints. In this scenario, the user wishe…
Secure Embedding Aggregation for Federated Representation Learning
Jiaxiang Tang, Jinbao Zhu, Songze Li +1
We consider a federated representation learning framework, where with the assistance of a central server, a group of distributed clients train collaboratively over their privat…
Information-Theoretically Private Matrix Multiplication From MDS-Coded Storage
Jinbao Zhu, Songze Li, Jie Li
We study two problems of private matrix multiplication, over a distributed computing system consisting of a master node, and multiple servers that collectively store a family of pu…
Generalized Lagrange Coded Computing: A Flexible Computation-Communication Tradeoff for Resilient, Secure, and Private Computation
Jinbao Zhu, Hengxuan Tang, Songze Li +1
We consider the problem of evaluating arbitrary multivariate polynomials over a massive dataset containing multiple inputs, on a distributed computing system with a master node and…
A Systematic Approach towards Efficient Private Matrix Multiplication
Jinbao Zhu, Songze Li
We consider the problems of Private and Secure Matrix Multiplication (PSMM) and Fully Private Matrix Multiplication (FPMM), for which matrices privately selected by a master node a…
Multi-User Blind Symmetric Private Information Retrieval from Coded Servers
Jinbao Zhu, Qifa Yan, Xiaohu Tang
The problem of Multi-user Blind -secure -colluding Symmetric Private Information Retrieval from Maximum Distance Separable (MDS) coded storage system with Byzantine and $…
Improved Constructions for Secure Multi-Party Batch Matrix Multiplication
Jinbao Zhu, Qifa Yan, Xiaohu Tang
This paper investigates the problem of Secure Multi-party Batch Matrix Multiplication (SMBMM), where a user aims to compute the pairwise products $\mathbf{A}\divideontimes\mathbf{B…
Capacity-Achieving Private Information Retrieval Schemes from Uncoded Storage Constrained Servers with Low Sub-packetization
Jinbao Zhu, Qifa Yan, Xiaohu Tang +1
This paper investigates reducing sub-packetization of capacity-achieving schemes for uncoded Storage Constrained Private Information Retrieval (SC-PIR) systems. In the SC-PIR syste…
Symmetric Private Polynomial Computation From Lagrange Encoding
Jinbao Zhu, Qifa Yan, Xiaohu Tang +1
The problem of -secure -colluding symmetric Private Polynomial Computation (PPC) from coded storage system with Byzantine and unresponsive servers is studied in this…
A new Capacity-Achieving Private Information Retrieval Scheme with (Almost) Optimal File Length for Coded Servers
Jinbao Zhu, Qifa Yan, Chao Qi +1
In a distributed storage system, private information retrieval (PIR) guarantees that a user retrieves one file from the system without revealing any information about the identity…