Federated k-Core Decomposition: A Secure Distributed Approach
<|reference_start|>Federated k-Core Decomposition: A Secure Distributed Approach: 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 distributed networks, e.g., Decentralized Online Social Networks (DOSNs) such that each vertex is a client as a single computing unit, the distributed $k$-core decomposition algorithms are already 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.<|reference_end|>
@article{guo2024federated,
    title={Federated k-Core Decomposition: A Secure Distributed Approach},
    author={Bin Guo, Emil Sekerinski, Lingyang Chu},
    journal={arXiv preprint arXiv:2410.02544},
    year={2024},
    archivePrefix={arXiv},
    eprint={2410.02544},
    primaryClass={cs.DC}
}