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Achieving O(log³n) Communication-Efficient Privacy-Preserving Range Query in Fog-Based IoT

范围查询(数据库) 计算机科学 同态加密 架空(工程) 差别隐私 计算机网络 加密 方案(数学) 查询优化 萨尔盖博 查询扩展 查询语言 航程(航空) Web搜索查询 数据库 情报检索 数据挖掘 搜索引擎 操作系统 数学分析 数学 复合材料 材料科学
作者
Hassan Mahdikhani,Rongxing Lu,Yandong Zheng,Jun Shao,Ali A. Ghorbani
出处
期刊:IEEE Internet of Things Journal [Institute of Electrical and Electronics Engineers]
卷期号:7 (6): 5220-5232 被引量:69
标识
DOI:10.1109/jiot.2020.2977253
摘要

The advance of Internet-of-Things (IoT) techniques has promoted an increasing number of organizations to explore more mission-critical solutions. However, the response latency, bandwidth usage, and reliability are still challenging issues in the traditional IoT. To tackle these challenges, the fog-based IoT has become popular and the range query is one of the most frequently used operations in fog-based IoT, where given a range query, a fog node will return the aggregated data from IoT devices to the query user. Because the fog nodes are not fully trusted, there is a desire to design a privacy-preserving range query scheme in the fog-based IoT. However, most of existing privacy-preserving range query schemes are not efficient in terms of communication overhead, especially for a large-size range. Therefore, it is still a challenging issue to design a communication-efficient range query in fog-based IoT. Aiming at this challenge, in this article, we propose a new privacy-preserving range query scheme in the fog-based IoT. Specifically, we first devise an efficient homomorphic encryption scheme for maintaining data privacy and security in a range query. Then, we present a novel range decomposition technique to compile the range query, which can transform a given range query [L, U], where 0 ≤ L ≤ U ≤ n - 1, into a semi-triangular structure, and enable our proposed scheme to achieve O(log 3 n) communication efficiency. The detailed security analysis shows that our proposed scheme is really privacy preserving, and the extensive performance evaluation demonstrates that our proposed scheme is efficient in terms of low communication overhead and the computational cost.
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