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Zhipeng Liu 0006

dblp:68/649-6 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
0009-0005-9234-9000ORCID · conflict

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Query processing and optimization · 100%
Network and information security
1 paper
Privacy and data protection · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Query processing and optimization › secure query processing
equi-join over encrypted data
0.912025
Practical Equi-Join Over Encrypted Database With Reduced Leakage · IEEE Trans. Knowl. Data Eng. 2025
Query processing and optimization
join processing
0.912025
Practical Equi-Join Over Encrypted Database With Reduced Leakage · IEEE Trans. Knowl. Data Eng. 2025
Privacy and data protection › privacy-preserving query processing
encrypted query processing
0.912025
Practical Equi-Join Over Encrypted Database With Reduced Leakage · IEEE Trans. Knowl. Data Eng. 2025

Methods — techniques the papers use, named apart from their topics

symmetric-key encryption · 1.7nonlinear transformation · 1.7cross-tags · 1.7
YearPublicationVenuePosition
2025 Practical Equi-Join Over Encrypted Database With Reduced Leakage
abstract
Secure join schemes, an important class of queries over encrypted databases, have attracted increasing attention. While efficient querying is paramount, data owners also emphasize the significance of privacy preservation. The state-of-the-art JXT (Jutla and Patranabis ASIACRYPT 2022) enables efficient join queries over encrypted tables with a symmetric-key solution. However, we observe that JXT inadvertently leaks undesirable query results as the number of queries increases. In this paper, we propose a novel equi-join scheme, One-Time Join Cross-Tags (OTJXT), which can avoid additional result leakage in multiple queries and extend to equi-join as opposed to natural join in JXT. Specifically, we design a new data encoding method using nonlinear transformations that reveals only the union of results for each query without extra leakage observed in JXT. Moreover, OTJXT addresses the linear search complexity issue (Shafieinejad et al. ICDE 2022) while preventing multiple query leakage. Finally, we implement OTJXT and compare its performance with JXT and Shafieinejad et al.'s scheme on the TPC-H dataset. The results show that OTJXT outperforms in search and storage efficiency, achieving a$\mathbf {98.5\times }$(resp.,$\mathbf {10^{6}\times }$) speedup in search latency and reducing storage cost by 62.5% (resp., 78.5%), compared to JXT (resp., Shafieinejad et al.'s scheme). Using OTJXT, a TPC-H query on a 40 MB database only takes 21 ms.
Qiaoer Xu, Jianfeng Wang 0001, Shifeng Sun 0001, Zhipeng Liu 0006, Xiaofeng Chen 0001
IEEE Trans. Knowl. Data Eng.4