Security and Privacy in Location-Based Service

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 31 August 2025 | Viewed by 2607

Special Issue Editors


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Guest Editor
Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320317, Taiwan
Interests: deep learning; databases; intelligent transportation; network security

E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320317, Taiwan
Interests: AI security; federated learning; AI+X applications

E-Mail Website
Guest Editor
Department of Computer Science and Information Engineering, National Central University, Taoyuan City 320317, Taiwan
Interests: security in cyber–physical systems; differential privacy; autonomous agent scheduling

Special Issue Information

Dear Colleagues,

Location-based service (LBS) technologies have grown dramatically in popularity in recent years thanks to the advance of technology in the fields of wireless communication, localization, and the internet of things (IoT). By collecting geographic data and information, these devices provide a variety of services such as navigation service, indoor/outdoor object searching, location-based advertising, and recommendation systems. A typical LBS requires the establishment of a bi-directional channel between the user and server, and the exchange of data often includes sensitive location information, a reality which potentially brings security and privacy leakage issues. Unfortunately, most vendors prioritize the quality of service over the security and user privacy of LBSs, leading to a situation where the user’s devices are riddled with security vulnerabilities in practice. Hence, LBSs are often exposed to attacks that possess the capacity to easily leak users' location privacy to attackers. This damage can be harmful to users. For example, disclosing a user's location information allows an external attacker to analyze the spatial–temporal relationship and obtain private information in advance, such as routine schedule, occupation, income, health condition, etc.

Given the importance of privacy, managing LBSs while preserving user location privacy has risen as a popular research topic. Some studies have investigated and explored location privacy issues in various applications, such as 4G and 5G cellular networks, wireless sensor networks (WSNs), IoT networks, control and network systems, cognitive radio networks, self-organizing networks, and so on. However, research into location privacy-preserving mechanisms is relatively lacking. Privacy leaks from both attack and defense remains an open area of research, especially in light of the challenge of privacy protection with the integration of LBSs and other thriving technologies.

This Special Issue aims to cover recent findings on theoretical advancement and practical challenges on lbs in recent architectures such as WSN, IoT networks, 5G, 6G, and so on. Offensive and defensive applications combined with machine learning technology or differential privacy mechanism are the potential subjects of research articles. Topics of interest include, but are not limited to:

  • Secure and location privacy-preserving protocol design in LBS;
  • Location privacy-preserving mechanism for LBS;
  • Secure and robust LBS in 5G, 6G, IoT, WSN, or radio network;
  • Secure and robust LBS in vehicular network;
  • The trade-off between privacy budget and utility in LBS;
  • Privacy-preserving in high-speed and low-latency network;
  • Decentralized LBS.

Prof. Dr. Min-Te Sun
Dr. Chia-Yu Lin
Dr. Hao-Tsung Yang
Guest Editors

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Keywords

  • location privacy
  • location-based services
  • privacy-preserving mechanism
  • cybersecurity
  • trustworthiness

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Published Papers (3 papers)

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Research

19 pages, 1324 KiB  
Article
How Precisely Can One Infer the Position of a Wi-Fi RTT Device by Eavesdropping on Its FTM Frames?
by Enrica Zola and Olga León
Electronics 2025, 14(8), 1540; https://doi.org/10.3390/electronics14081540 - 10 Apr 2025
Viewed by 150
Abstract
Until the implementation of the IEEE 802.11az standard in common devices becomes a reality, the IEEE 802.11mc fine time measurement (FTM) procedure used for location purposes in indoor environments may be easily compromised by an adversary. Despite the scarce amount of work focusing [...] Read more.
Until the implementation of the IEEE 802.11az standard in common devices becomes a reality, the IEEE 802.11mc fine time measurement (FTM) procedure used for location purposes in indoor environments may be easily compromised by an adversary. Despite the scarce amount of work focusing on the security of the FTM procedure, in the first place, this paper provides an overview of the vulnerabilities that have been studied so far. Lack of encryption and authentication allows an attacker to eavesdrop on any FTM session and/or forge the frame exchange. But how critical can this be? We study the situation where an adversary is able to overhear the FTM frames of a legitimate user that is positioning itself. On the one hand, we show that the adversary is able to easily infer the position of the victim. Moreover, simulation results show that this calculated position can be obtained with a 99th percentile error of 1 m even under the presence of errors in the time measurements, raising significant concern about the security of the current implementation of the protocol. Full article
(This article belongs to the Special Issue Security and Privacy in Location-Based Service)
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19 pages, 402 KiB  
Article
From Vulnerability to Resilience: Securing Public Safety GPS and Location Services with Smart Radio, Blockchain, and AI-Driven Adaptability
by Swarnamouli Majumdar and Anjali Awasthi
Electronics 2025, 14(6), 1207; https://doi.org/10.3390/electronics14061207 - 19 Mar 2025
Viewed by 391
Abstract
In an era where public safety hinges on real-time intelligence and rapid response, this paper delves into the pivotal role of location-based services (LBSs) in empowering law enforcement and fire rescue operations. GPS tracking systems have revolutionized situational awareness and resource management, yet [...] Read more.
In an era where public safety hinges on real-time intelligence and rapid response, this paper delves into the pivotal role of location-based services (LBSs) in empowering law enforcement and fire rescue operations. GPS tracking systems have revolutionized situational awareness and resource management, yet they come with critical security and privacy challenges, including unauthorized access, real-time data interception, and insider threats. To address these vulnerabilities, this study introduces an innovative framework that combines blockchain, artificial intelligence (AI), and IoT technologies to redefine emergency management and public safety systems. Voice-command virtual assistants powered by AI enable hands-free operations, enhance hazard detection, and optimize resource allocation in real time, while blockchain’s decentralized and tamper-proof architecture ensures data integrity and security. By integrating these cutting-edge technologies, the research showcases a system design that not only secures sensitive information but also drives operational efficiency and resilience. With applications spanning smart cities, autonomous systems, and fire rescue operations, this study offers a transformative vision for public safety, emphasizing technology integration, digital innovation, and trust-building. These advancements promise not only to protect responders and communities but also to redefine the standards of security and efficiency in modern emergency management. Full article
(This article belongs to the Special Issue Security and Privacy in Location-Based Service)
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22 pages, 978 KiB  
Article
Cloud-Based Access Control Including Time and Location
by Mustafa Al Lail, Marshal Moncivais, Robert Benton and Alfredo J. Perez
Electronics 2024, 13(14), 2812; https://doi.org/10.3390/electronics13142812 - 17 Jul 2024
Viewed by 1348
Abstract
Location-based services (LBS) offer various functionalities, but ensuring secure access to sensitive user data remains a challenge. Traditional access control methods often need more detail to enforce location-specific restrictions. This paper proposes a new approach that utilizes the Generalized Spatio-Temporal Role-Based Access Control [...] Read more.
Location-based services (LBS) offer various functionalities, but ensuring secure access to sensitive user data remains a challenge. Traditional access control methods often need more detail to enforce location-specific restrictions. This paper proposes a new approach that utilizes the Generalized Spatio-Temporal Role-Based Access Control Model (GSTRBAC) within the context of LBS. GSTRBAC grants access based on user credentials, authorized locations, and access times, providing a detailed approach to securing LBS data. We introduce an optimized cloud-based GSTRBAC implementation suitable for deployment in modern LBS architectures. The system uses two secure communication protocols tailored to different security requirements. This allows for efficient communication for less-sensitive data while offering robust protection for highly sensitive information. Additionally, a proof-of-concept mobile application demonstrates the system’s functionality and efficiency within an LBS environment. Our evaluation confirms the effectiveness of the cloud-based GSTRBAC implementation in enforcing location-specific access control while maintaining resource and time efficiency. Full article
(This article belongs to the Special Issue Security and Privacy in Location-Based Service)
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