# Secure Clustered Distributed Storage Against Eavesdroppers

## TL;DR

This paper introduces new eavesdropper models tailored for clustered distributed storage systems and derives upper bounds on secure data storage, providing coding schemes that achieve these bounds under certain conditions.

## Contribution

It proposes two novel eavesdropper models for clustered DSSs and develops optimal coding schemes to maximize secure storage capacity.

## Key findings

- Upper bounds on securely storable data for each eavesdropper model.
- A network coding scheme achieving the upper bound for the node-restricted model.
- Conditions under which the coding scheme is optimal.

## Abstract

This paper considers the security issue of practical distributed storage systems (DSSs) which consist of multiple clusters of storage nodes. Noticing that actual storage nodes constituting a DSS are distributed in multiple clusters, two novel eavesdropper models - the node-restricted model and the cluster-restricted model - are suggested which reflect the clustered nature of DSSs. In the node-restricted model, an eavesdropper cannot access the individual nodes, but can eavesdrop incoming/outgoing data for $L_c$ compromised clusters. In the cluster-restricted model, an eavesdropper can access a total of $l$ individual nodes but the number of accessible clusters is limited to $L_c$. We provide an upper bound on the securely storable data for each model, while a specific network coding scheme which achieves the upper bound is obtained for the node-restricted model, given some mild condition on the node storage size.