Secure kNN query of outsourced spatial data using two-cloud architecture

Article Computer Science, Information Systems

Privacy-Preserving KNN Classification Algorithm for Smart Grid

Zhuhuan Song et al.

Summary: This paper proposes a privacy-preserving KNN classification algorithm, which is implemented with a single cloud server. It protects the privacy of smart meters and control centers, while keeping the classification results private for the server. The algorithm is more efficient compared to the original KNN and is suitable for small devices in IoT.

SECURITY AND COMMUNICATION NETWORKS (2022)

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Proceedings Paper Computer Science, Hardware & Architecture

Lightweight Privacy-Preserving Spatial Keyword Query over Encrypted Cloud Data

Yutao Yang et al.

Summary: This paper presents an enhanced spatial keyword query scheme that utilizes random numbers and a random permutation to enhance encryption security. Furthermore, a privacy-preserving spatial keyword query scheme is proposed based on the enhanced encryption scheme and the Geohash algorithm. Additionally, a lightweight spatial keyword query scheme is designed by using a unified index for query, reducing storage and computational costs.

2022 IEEE 42ND INTERNATIONAL CONFERENCE ON DISTRIBUTED COMPUTING SYSTEMS (ICDCS 2022) (2022)

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Article Computer Science, Information Systems

Constrained top-k nearest fuzzy keyword queries on encrypted graph in road network

Fangyuan Sun et al.

Summary: As road networks grow, outsourcing large-scale graphs to the cloud improves query efficiency and reduces user burden. However, to protect data privacy, graphs must be encrypted before uploading to the cloud.

COMPUTERS & SECURITY (2021)

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Article Computer Science, Interdisciplinary Applications