A Survey on Privacy in Location-Based Services

Zurbarán, Mayra; González, Liliana Rodríguez; Wightman, Pedro M.; Labrador, Miguel A.

doi:10.14482/inde.32.2.6128

Cited by 13 publications

(6 citation statements)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The Pinwheel method was designed for applications that constantly keep track and update the users' location to a service provider (Wightman, Zurbaran, & Santander, 2014; Wightman et al., 2013; Zurbarán, Ávila, Wightman, & Fernández, 2014; Zurbarán, González, Wightman Rojas, & Labrador, 2014) and is a modified randomization method. In the Pinwheel method, the obfuscated point is a random point or either the farthest or the middle point among N random points in a pinwheel shape with center the original point P and radius r (Figure 1e).…”

Section: Existing Methods and Related Workmentioning

confidence: 99%

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

Nowbakht

O’Sullivan

Cawkwell

et al. 2022

Transactions in GIS

View full text Add to dashboard Cite

A major challenge of sharing spatially explicit agricultural and agri‐environmental data is to identify the trade‐off between field parcel confidentiality and spatial pattern preservation. In this work, 27 point‐based obfuscation and evaluation methods were applied on agricultural data, collected by the Irish Nutrient Management Planning Online (NMP Online) platform, which is a high‐density polygon dataset developed to inform precision agriculture through nutrient management based on soil fertility and agronomic targets. Broad categorizations of methods—including N*Rand, Donut, Density, Pinwheel, AHilb, and k‐anonymity—were developed, combined, and modified to achieve the best trade‐off between security and accuracy. To improve geoprivacy and spatial pattern preservation of existing Donut and Density methods, qualitative approaches, including Donut‐k and Density‐k methods, were introduced which identify the optimal values of radii based on a combination of the Donut method and k‐anonymity satisfaction, and subsequently optimal k‐anonymity determination. Modified AHilb and Donut‐AHilb methods were also developed to generate smaller and arbitrary obfuscation areas to improve location security. The Donut‐AHilb method was found to be the best at spatial pattern preservation and satisfying larger k‐anonymity, but the risk of false identification and non‐unique obfuscation was high when considering the polygon nature of agricultural data such as field parcels. Further, we introduce the term “non‐unique obfuscated points,” which is important when obfuscating static objects as two or more points might have the same obfuscated location, which has relevance to the wider GIScience community.

show abstract

Section: Existing Methods and Related Workmentioning

confidence: 99%

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

Nowbakht

O’Sullivan

Cawkwell

et al. 2022

Transactions in GIS

View full text Add to dashboard Cite

show abstract

“…They vary in the requirements for implementation, processing time, communication resources, architecture, privacy provided and the kind of LBS that may be supported. In Yiu, Lu, and Jensen (2009) and Zurbarán, Gonzalez, Wightman, and Labrador (2014), surveys of different techniques for location privacy are presented.…”

Section: Location Privacy Protection Mechanismsmentioning

confidence: 99%

NRand‐K: Minimizing the impact of location obfuscation in spatial analysis

Zurbarán

Wightman

Brovelli

et al. 2018

Transactions in GIS

Self Cite

View full text Add to dashboard Cite

Location privacy, or geoprivacy, is critical to secure users’ privacy in context‐aware applications. Location‐based services pose privacy risks for users, due to the inferences that could be made about them from their location information and the potential misuse of this data by service providers or third‐party companies. A common solution is to apply masking or location obfuscation, which degrades location information quality while keeping a geographic coordinate structure. However, there is a trade‐off between privacy, quality of service, and quality of information, the last one being a valuable asset for companies. NRand is a location privacy mechanism with obfuscation capabilities and resistance against filtering attacks. In order to minimize the impact on location information quality, NRand‐K has been introduced. This algorithm is designed for use when releasing location information to third parties or as open data with privacy concerns. To assess the impact of location obfuscation on exploratory spatial data analysis (ESDA), a comparison is performed between obfuscated data with NRand, NRand‐K, and unaltered data. For the experiments, geolocated tweets collected during the Central Italy 2016 earthquake are used. Results show that NRand‐K reduces the impact on ESDA, where inferences were similar to those obtained with the unaltered data.

show abstract

“…Regarding location privacy, some techniques based on obfuscation have been developed. In [3], the authors present a compendium of techniques to protect the location privacy of the users. In [13], the authors propose an approach based on entity resolution which enables users to disclose their mobility information without compromising their privacy, even the data are linked with external publicly available information (social networks).…”

Section: Related Workmentioning

confidence: 99%

“…Location-based information systems (LBISs) are defined as "applications that provide users with information based on their geographical position, which could be obtained from the mobile device they are accessing the service, or using a manually defined location" [2]. For LBSs to provide the requested information properly, sensitive data about the subject's location is required [3]. Location information privacy is an important topic in the context of expanding mobile technologies and applications.…”

Section: Introductionmentioning

confidence: 99%

Privacy perception in location-based services for mobile devices in the university community of the north coast of Colombia

Gamarra¹,

Fuentes²,

Calabria-Sarmiento³

et al. 2019

IyU

View full text Add to dashboard Cite

Introduction: The use of mobile applications has increased in the last years. Most of them require the knowledge of the user location, either for their core service or for marketing purposes. Location-based services (LBS) offer context-based assistance to users based on their location. Although these applications ask the user for permission to use their location and even explain in detail how this information will be used in its terms and conditions, most users are not aware or even interested in the fact that their location information is stored in databases and monetized by selling it to third-party companies. Regarding this situation, we developed a study with the aim to assess perception, concerns and awareness from users about their location information. Methods: This work is based on an exploratory survey applied to the university community, mainly from the North Coast of Colombia, to measure the perception of location privacy of users with mobile devices. The questionnaire was applied using Google Forms. The survey has nineteen questions organized in three sections: personal information, identification of privacy and privacy management. These questions were designed to know the users’ perceptions of privacy concerns in LBS and any actions they take to preserve it. Results: The results show that, in general, the respondents do not have a real concern regarding the privacy of their geolocation data, and the majority is not willing to pay to protect their privacy. Conclusions: This type of surveys can generate awareness among participants about the use of their private information. The results expose in this paper can be used to create government policies and regulations by technology companies about the privacy management.

show abstract

A Survey on Privacy in Location-Based Services

Abstract: A Survey on PrivAcy in LocAtion-BASed ServiceS

Cited by 13 publications

References 44 publications

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

A comparison of obfuscation methods used for privacy protection: Exploring the challenges of polygon data in agricultural research

NRand‐K: Minimizing the impact of location obfuscation in spatial analysis

Privacy perception in location-based services for mobile devices in the university community of the north coast of Colombia

Contact Info

Product

Resources

About