Mikael Skoglund

The $\epsilon$-error Capacity of Symmetric PIR with Byzantine Adversaries

2018 · arXiv (Cornell University)

The capacity of symmetric private information retrieval with $K$ messages, $N$ servers (out of which any $T$ may collude), and an omniscient Byzantine adversary (who can corrupt any $B$ answers) is shown to be $1 …

Secure symmetric private information retrieval from colluding databases with adversaries

2017

The problem of symmetric private information retrieval (SPIR) from replicated databases with colluding servers and adversaries is studied. Specifically, the database comprises K files, which are replicatively stored among N servers. A user wants to …

Symmetric Private Information Retrieval with Mismatched Coded Messages and Randomness

2019

The capacity of symmetric private information retrieval (PIR) with N servers and K messages, each coded by an (N, M)-MDS code has been characterized as CMDS-SPIR= 1- M/N . A critical assumption for this result …

Private Variable-Length Coding with Zero Leakage

2023 · arXiv (Cornell University)

A private compression design problem is studied, where an encoder observes useful data $Y$, wishes to compress it using variable length code and communicates it through an unsecured channel. Since $Y$ is correlated with private …

Gradient Coding in Decentralized Learning for Evading Stragglers

2024 · arXiv (Cornell University)

In this paper, we consider a decentralized learning problem in the presence of stragglers. Although gradient coding techniques have been developed for distributed learning to evade stragglers, where the devices send encoded gradients with redundant …

Adaptive Coded Federated Learning: Privacy Preservation and Straggler Mitigation

2024 · arXiv (Cornell University)

In this article, we address the problem of federated learning in the presence of stragglers. For this problem, a coded federated learning framework has been proposed, where the central server aggregates gradients received from the …