Federated k-Core Decomposition: A Secure Distributed Approach

TL;DR

This paper introduces a secure, distributed algorithm for k-core decomposition in decentralized social networks, addressing privacy and security concerns in graph analysis.

Contribution

It presents the first secure distributed k-core decomposition algorithm, enhancing privacy protection in decentralized network analysis.

Findings

First secure distributed k-core decomposition algorithm proposed

Improves privacy and security in decentralized graph analysis

Applicable to privacy-sensitive networks like DOSNs

Abstract

As one of the most well-studied cohesive subgraph models, the $k$-core is widely used to find graph nodes that are ``central'' or ``important'' in many applications, such as biological networks, social networks, ecological networks, and financial networks. For Decentralized Online Social Networks (DOSNs), where each vertex is a client as a single computing unit, distributed k-core decomposition algorithms have already been proposed. However, current distributed approaches fail to adequately protect privacy and security. In today's data-driven world, data privacy and security have attracted more and more attention, e.g., DOSNs are proposed to protect privacy by storing user information locally without using a single centralized server. In this work, we are the first to propose the secure version of the distributed $k$-core decomposition.