Achieving efficient and secure keyword attribute community search on cloud servers

Ziyang Zhong; Pan Chang; Min Cai

doi:10.1117/12.3038169

22 August 2024 Achieving efficient and secure keyword attribute community search on cloud servers

Ziyang Zhong, Pan Chang, Min Cai

Proceedings Volume 13228, Fifth International Conference on Computer Communication and Network Security (CCNS 2024); 132281Z (2024) https://doi.org/10.1117/12.3038169
Event: Fifth International Conference on Computer Communication and Network Security (CCNS 2024), 2024, Guangzhou, China

Abstract

Community search is a technique used to identify and retrieve groups of nodes with specific attributes or associations by analyzing the connections between nodes in a network or graph structure. Existing researches mainly focus on single secure search requirements, making it difficult to support complex graph searches. Therefore, this paper proposes a secure search scheme that simultaneously satisfies k-core and keyword attribute similarity requirements. Specifically, to enhance search efficiency, we utilize an improved core decomposition tree to index community graph containing keyword attributes. Additionally, based on the triangle inequality, we design an efficient pruning strategy. To enhance security, Paillier homomorphic encryption and matrix encryption are adopted, presenting a secure and efficient attribute community search scheme that protects the privacy of outsourced data, query requests, and query results. Security analysis and performance evaluation demonstrate that our proposed solution is both secure and efficient.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Ziyang Zhong, Pan Chang, and Min Cai "Achieving efficient and secure keyword attribute community search on cloud servers", Proc. SPIE 13228, Fifth International Conference on Computer Communication and Network Security (CCNS 2024), 132281Z (22 August 2024); https://doi.org/10.1117/12.3038169

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