activity
20242026
most citedCode-Based Single-Server Private Information Retrieval: Circumventing the Sub-Query Attack

2 citations · 2 across the 7 of their papers we have counts for

collaborators

7 papers

cs.IT2026

Algebraic Geometry Codes Approach the Half-Singleton Bound with Constant Field Size

Neehar Verma, Camilla Hollanti, Razane Tajeddine

We study linear codes for insertion and deletion (insdel) errors through the lens of evaluation codes. We develop a general framework for analyzing random puncturings of evaluation…

cs.IT2025

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…

cs.IR2025

CB-cPIR: Code-Based Computational Private Information Retrieval

Camilla Hollanti, Neehar Verma

A private information retrieval (PIR) scheme is a protocol that allows a user to retrieve a file from a database without revealing the identity of the desired file to a curious dat…

cs.IT2024

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…

cs.IT2024

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…

cs.LG2024

Approximate Gradient Coding for Privacy-Flexible Federated Learning with Non-IID Data

Okko Makkonen, Sampo Niemelä, Camilla Hollanti +1

This work focuses on the challenges of non-IID data and stragglers/dropouts in federated learning. We introduce and explore a privacy-flexible paradigm that models parts of the cli…