Verifiable Strong Privacy-Preserving Any-Hop Reachability Query on Blockchain-Assisted Cloud

Any-hop (k-hop) reachability query is one fundamental operation in graph data analysis and its performance affects the efficiency of various tasks in Social Internet of Things. As graph data scale increases, data is often outsourced to cloud servers. To protect the privacy of graph data, it is necessary to encrypt the data before outsourcing. Existing schemes can only support privacy-preserving 2-hop reachability queries. Only one scheme can support privacy-preserving k-hop reachability queries, but it discloses topological information and the query results is not verifiable. Most serious deficiency is that its efficiency is not practical. To address these issues, we propose a verifiable strong privacy-preserving k-hop reachability query on encrypted data. This scheme not only supports efficient privacy-preserving k-hop reachability queries without leaking any network topological information but also uses blockchain to achieve verifiability of query results. The security analysis shows that our scheme is secure. Compared to existing k-hop reachability query scheme, our scheme greatly improves query efficiency (at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.4\cdot 10^{5}\times $ </tex-math></inline-formula> faster when the number of nodes <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n \geq 100$ </tex-math></inline-formula> ).

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Publication Details

Journal
IEEE Internet of Things Journal
Published
2024-08-19
DOI
https://doi.org/10.1109/jiot.2024.3445431
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Verifiable Strong Privacy-Preserving Any-Hop Reachability Query on Blockchain-Assisted Cloud

Shundong Li, Jingjuan Yu, Yuwei Duan, Ping Luo
IEEE Internet of Things Journal
Cryptography and Data Security
article

Verifiable Strong Privacy-Preserving Any-Hop Reachability Query on Blockchain-Assisted Cloud

Shundong Li, Jingjuan Yu, Yuwei Duan, Ping Luo
article en

Abstract

Any-hop (k-hop) reachability query is one fundamental operation in graph data analysis and its performance affects the efficiency of various tasks in Social Internet of Things. As graph data scale increases, data is often outsourced to cloud servers. To protect the privacy of graph data, it is necessary to encrypt the data before outsourcing. Existing schemes can only support privacy-preserving 2-hop reachability queries. Only one scheme can support privacy-preserving k-hop reachability queries, but it discloses topological information and the query results is not verifiable. Most serious deficiency is that its efficiency is not practical. To address these issues, we propose a verifiable strong privacy-preserving k-hop reachability query on encrypted data. This scheme not only supports efficient privacy-preserving k-hop reachability queries without leaking any network topological information but also uses blockchain to achieve verifiability of query results. The security analysis shows that our scheme is secure. Compared to existing k-hop reachability query scheme, our scheme greatly improves query efficiency (at least <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$6.4\cdot 10^{5}\times $ </tex-math></inline-formula> faster when the number of nodes <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$n \geq 100$ </tex-math></inline-formula> ).

IEEE Internet of Things JournalVol. 11(24)
Shaanxi Normal University (CN), Tsinghua University (CN)
National Key Research and Development Program of China
Openalex Percentile: Top 89%
Cryptography and Data Security
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Verifiable Strong Privacy-Preserving Any-Hop Reachability Query on Blockchain-Assisted Cloud — Shundong Li, Jingjuan Yu, et al. · IEEE Internet of Things Journal (2024) | TGRS Research Map | TGRS