Federated k-Core Decomposition: A Secure Distributed Approach

Fuente: arXiv
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Autores principales: Guo, Bin, Sekerinski, Emil, Chu, Lingyang
Formato: Preprint
Publicado: 2024
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author Guo, Bin
Sekerinski, Emil
Chu, Lingyang
author_facet Guo, Bin
Sekerinski, Emil
Chu, Lingyang
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2410_02544
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Federated k-Core Decomposition: A Secure Distributed Approach
Guo, Bin
Sekerinski, Emil
Chu, Lingyang
Distributed, Parallel, and Cluster Computing
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.
title Federated k-Core Decomposition: A Secure Distributed Approach
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2410.02544