4.8 Article

Privacy-Preserving Location-Based Data Queries in Fog-Enhanced Sensor Networks

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 9, Issue 14, Pages 12285-12299

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2021.3135303

Keywords

Cryptography; Cloud computing; Internet of Things; Homomorphic encryption; Performance evaluation; Data privacy; Servers; Fog computing; Internet of Things (IoT); privacy-preserving data queries; somewhat homomorphic encryption (SHE); trusted execution environment

Funding

  1. Fundamental Research Funds for the Central Universities [2020NTST32]
  2. Research Grants Council of Hong Kong [CityU 11202419]
  3. National Natural Science Foundation of China [61732022, 62102035]

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This article presents a privacy-preserving-location-based data query scheme in fog-enhanced sensor networks by utilizing somewhat homomorphic encryption technology to protect user privacy while allowing cloud and fog devices to collect sensor data from specific areas. It implements a secure and efficient matched data extraction scheme and system prototype, and evaluates it in the software guard extension environment.
Fog computing has emerged as a promising framework with the rapid growth of the Internet of Things (IoT). In fog computing, the new entity, named fog device, can help the cloud process the large amount of data generated by IoT devices. Along with this trend, a location-based query scheme that collects IoT devices' data from specific areas is an important application, especially in fog-enhanced sensor networks. However, in this application, the cloud and fog devices require the user's query, sensors' locations, and sensor data so that it raises critical privacy and security concerns. In this article, we devise a privacy-preserving-location-based data query scheme in fog-enhanced sensor networks, which allows the cloud and fog devices to collect sensor data from a query area without learning the three kinds of information. Specifically, we resort to a cryptographic primitive, named somewhat homomorphic encryption (SHE), with ciphertext packing to encrypt query, locations, and sensor data and efficiently calculate the distances between the user's query and sensors. Then, we show how to build a hardware-assisted data query scheme to extract the matched data based on the distances. We formally analyze the security strengths and implement the system prototype. In order to implement secure processing within software guard extension (SGX), we make an effort to adapt the existing mathematical libraries to the advanced SGX trusted environment. Evaluation results demonstrate that our proposed design is secure and efficient.

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