7 citations · 9 across the 11 of their papers we have counts for
9 papers · 1 filter
Analog Secure Distributed Matrix Multiplication
Okko Makkonen, Camilla Hollanti
In this paper, we present secure distributed matrix multiplication (SDMM) schemes over the complex numbers with good numerical stability and small mutual information leakage by uti…
A Matrix Completion Approach for the Construction of MDP Convolutional Codes
Sakshi Dang, Julia Lieb, Okko Makkonen +2
Maximum Distance Profile (MDP) convolutional codes are an important class of channel codes due to their maximal delay-constrained error correction capabilities. The design of MDP c…
Secret Sharing for Secure and Private Information Retrieval: A Construction Using Algebraic Geometry Codes
Okko Makkonen, David Karpuk, Camilla Hollanti
Private information retrieval (PIR) considers the problem of retrieving a data item from a database or distributed storage system without disclosing any information about which dat…
Algebraic Geometry Codes for Cross-Subspace Alignment in Private Information Retrieval
Okko Makkonen, David Karpuk, Camilla Hollanti
A new framework for interference alignment in secure and private information retrieval (PIR) from colluding servers is proposed, generalizing the original cross-subspace alignment…
Flexible Field Sizes in Secure Distributed Matrix Multiplication via Efficient Interference Cancellation
Okko Makkonen
In this paper, we propose a new secure distributed matrix multiplication (SDMM) scheme using the inner product partitioning. We construct a scheme with a minimal number of workers…
Algebraic Geometry Codes for Secure Distributed Matrix Multiplication
Okko Makkonen, Elif Saçıkara, Camilla Hollanti
In this paper, we propose a novel construction for secure distributed matrix multiplication (SDMM) based on algebraic geometry (AG) codes, which we call the PoleGap SDMM scheme. Th…
Secure Distributed Gram Matrix Multiplication
Okko Makkonen, Camilla Hollanti
The Gram matrix of a matrix is defined as (or ). Computing the Gram matrix is an important operation in many applications, such as linear regression with the lea…
General Framework for Linear Secure Distributed Matrix Multiplication with Byzantine Servers
Okko Makkonen, Camilla Hollanti
In this paper, a general framework for linear secure distributed matrix multiplication (SDMM) is introduced. The model allows for a neat treatment of straggling and Byzantine serve…
Efficient Recovery of a Shared Secret via Cooperation: Applications to SDMM and PIR
Jie Li, Okko Makkonen, Camilla Hollanti +1
This work considers the problem of privately outsourcing the computation of a matrix product over a finite field to helper servers. These servers are considered…