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Related Experiment Video

Updated: Jan 18, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
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Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

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Secure and Efficient Skyline Queries on Encrypted Data.

Jinfei Liu1, Juncheng Yang1, Li Xiong1

  • 1Department of Mathematics and Computer Science, Emory University, Atlanta, GA 30322.

IEEE Transactions on Knowledge and Data Engineering
|October 1, 2019
PubMed
Summary
This summary is machine-generated.

This study introduces a secure protocol for processing skyline queries on encrypted data in the cloud. It ensures data privacy while enabling efficient multi-criteria decision-making without revealing sensitive information.

Keywords:
Skylineefficientparallelsecuresemi-honest

Related Experiment Videos

Last Updated: Jan 18, 2026

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases
07:26

Executing Complexity-Increasing Queries in Relational MySQL and NoSQL MongoDB and EXist Size-Growing ISO/EN 13606 Standardized EHR Databases

Published on: March 19, 2018

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Area of Science:

  • Computer Science
  • Cryptography
  • Database Systems

Background:

  • Cloud computing offers cost-effective data storage and processing.
  • Protecting sensitive data (e.g., medical records) in the cloud is crucial.
  • Querying encrypted data securely and efficiently remains a significant challenge.

Purpose of the Study:

  • To develop a fully secure protocol for skyline queries over encrypted data.
  • To address the challenges of complex computations in skyline queries.
  • To ensure the cloud server gains no knowledge of the data, query, or results.

Main Methods:

  • Proposed a fully secure skyline query protocol using semantically-secure encryption.
  • Introduced a novel secure dominance protocol as a subroutine and building block.
  • Implemented optimizations including data partitioning and lazy merging to reduce computation.

Main Results:

  • Demonstrated the feasibility of secure skyline queries over encrypted data.
  • Empirically studied the protocol's efficiency and scalability through serial and parallel implementations.
  • Validated the effectiveness of data partitioning and lazy merging optimizations.

Conclusions:

  • The proposed protocol enables secure and efficient skyline queries on encrypted cloud data.
  • The secure dominance protocol is a versatile component for other encrypted data queries.
  • The optimizations significantly reduce computational load, enhancing practical usability.