Abstract
With the rapid development of GPS-equipped smart mobile devices and mobile computing, location-based services (LBS) are increasing in popularity in the Internet of Things (IoT). Although LBS provide enormous benefits to users, they inevitably introduce some significant privacy concerns. To protect user privacy, a variety of location privacy-preserving schemes have been recently proposed. Among these schemes, the dummy-based location privacy-preserving (DLP) scheme is a widely used approach to achieve location privacy for mobile users. However, the computation cost of the existing dummy-based location privacy-preserving schemes is too high to meet the practical requirements of resource-constrained IoT devices. Moreover, the DLP scheme is inadequate to resist against an adversary with side information. Thus, how to effectively select a dummy location is still a challenge. In this paper, we propose a novel lightweight dummy-based location privacy-preserving scheme, named the enhanced dummy-based location privacy-preserving(Enhanced-DLP) to address this challenge by considering both computational costs and side information. Specifically, the Enhanced-DLP adopts an improved greedy scheme to efficiently select dummy locations to form a k-anonymous set. A thorough security analysis demonstrated that our proposed Enhanced-DLP can protect user privacy against attacks. We performed a series of experiments to verify the effectiveness of our Enhanced-DLP. Compared with the existing scheme, the Enhanced-DLP can obtain lower computational costs for the selection of a dummy location and it can resist side information attacks. The experimental results illustrate that the Enhanced-DLP scheme can effectively be applied to protect the user’s location privacy in IoT applications and services.
Highlights
In recent years, with the rapid development of smart mobile devices and mobile communication technologies, Internet of Things (IoT) services have emerged in our daily life [1]
We propose an enhanced dummy-based location privacy-preserving scheme (Enhanced-DLP), which aims for practical efficiency for IoT users and devices with strong location privacy protection
The service map data of the location-based services (LBS) provider is divided into n × n cells and each cell has the same size for IoT users to submit queries
Summary
With the rapid development of smart mobile devices and mobile communication technologies, Internet of Things (IoT) services have emerged in our daily life [1]. Many potential IoT applications rely on location-based services (LBS) or LBS applications, such as GPS navigators, information retrieval, and context-aware mobile applications, etc. IoT applications, users can obtain the required geographic location services by sending their current location or point of Interest (POI) to the untrusted LBS providers (LSPs), for instance, querying to find the nearest shopping center [4]. LBS provides enormous convenience and benefits to IoT users, it raises serious privacy concerns because location information is collected by untrusted or malicious LSPs [4]. By analyzing users’ location information, untrusted or malicious LSPs can infer users’ personal information by associating a user’s identity with queried locations and interests [4], such as their home addresses, sexual preference and health conditions, etc.
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