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ObliuSky: Oblivious User-Defined Skyline Query Processing in the Cloud
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AI
DOI：10.1109/TSC.2024.3512945.png)
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Abstract
En 中文
The proliferation of cloud computing has spurred the popularity of storing and querying databases in the cloud. Among others, skyline queries play an important role in the database field due to its usefulness in multi-criteria decision support systems. To accommodate the tailored needs of users, user-defined skyline query has recently emerged, allowing users to define custom preferences in their skyline queries. However, user-defined skyline query services, if deployed in the cloud, may raise critical privacy concerns as the outsourced databases and skyline queries may contain proprietary/privacy-sensitive information. In light of the above, this paper presents ObliuSky, a new solution enabling oblivious user-defined skyline query processing in the cloud. ObliuSky departs from prior work by not only providing confidentiality protection for the content of the outsourced database, the user-defined skyline queries, and the query results, but also hiding the data patterns (e.g., user-defined dominance relations among database points and search access patterns) which may indirectly cause data leakages. We formally analyze the security guarantees and conduct extensive performance evaluations. The results show that while achieving much stronger security guarantees than the state-of-the-art prior work, ObliuSky is superior in database and query encryption efficiency, and scalable in oblivious query processing.
Keywords:
Databases
Cryptography
Query processing
Cloud computing
Protocols
Data privacy
Protection
Privacy
Performance evaluation
Hardware
database service outsourcing
privacy preservation
secure user-defined skyline query
Journal
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5.8
Papers:
2.1K
Citations:
6.5K
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