scholarly journals Privacy vs. Reward in Indoor Location-Based Services

2016 ◽  
Vol 2016 (4) ◽  
pp. 102-122 ◽  
Author(s):  
Kassem Fawaz ◽  
Kyu-Han Kim ◽  
Kang G. Shin
Keyword(s):  
Location Privacy ◽  
Indoor Localization ◽  
Service Providers ◽  
Location Based Services ◽  
Location Information ◽  
Privacy Concerns ◽  
Indoor Location ◽  
Location Data ◽  
Personalized Services ◽  
Privacy Risks

AbstractWith the advance of indoor localization technology, indoor location-based services (ILBS) are gaining popularity. They, however, accompany privacy concerns. ILBS providers track the users’ mobility to learn more about their behavior, and then provide them with improved and personalized services. Our survey of 200 individuals highlighted their concerns about this tracking for potential leakage of their personal/private traits, but also showed their willingness to accept reduced tracking for improved service. In this paper, we propose PR-LBS (Privacy vs. Reward for Location-Based Service), a system that addresses these seemingly conflicting requirements by balancing the users’ privacy concerns and the benefits of sharing location information in indoor location tracking environments. PR-LBS relies on a novel location-privacy criterion to quantify the privacy risks pertaining to sharing indoor location information. It also employs a repeated play model to ensure that the received service is proportionate to the privacy risk. We implement and evaluate PR-LBS extensively with various real-world user mobility traces. Results show that PR-LBS has low overhead, protects the users’ privacy, and makes a good tradeoff between the quality of service for the users and the utility of shared location data for service providers.

Location-Based Services

2011 ◽  
pp. 18-34 ◽  
Author(s):  
Ramaprasad Unni ◽  
Robert Harmon
Keyword(s):  
Value Chain ◽  
Business Models ◽  
Service Providers ◽  
Mobile Network ◽  
Location Based Services ◽  
Privacy Concerns ◽  
Location Data ◽  
Personalized Services ◽  
Wireless Users ◽  
Integral Role

Location-based services are expected to play an integral role in the mobile-commerce domain. Mobile network operators and service providers have the opportunity to add value and create additional revenue streams through a variety of personalized services based on location of individual wireless users. However, strategic thinking in this area is still evolving. Many issues surrounding location data such as ownership and their use by network operators and third parties, privacy concerns of consumers, and business models for these services are not well understood. This chapter provides (1) an overview of location-based wireless services and their related technologies, (2) an examination of the LBS value chain, and (3) strategic implications for network operators and service providers.

scholarly journals Complying with Privacy Legislation: From Legal Text to Implementation of Privacy-Aware Location-Based Services

2018 ◽  
Vol 7 (11) ◽  
pp. 442 ◽  
Author(s):  
Mehrnaz Ataei ◽  
Auriol Degbelo ◽  
Christian Kray ◽  
Vitor Santos
Keyword(s):  
Data Privacy ◽  
Location Privacy ◽  
Service Providers ◽  
Location Based Services ◽  
Legal Text ◽  
General Data Protection Regulation ◽  
Location Data ◽  
Privacy Laws ◽  
Technical Issues ◽  
General Data

An individual’s location data is very sensitive geoinformation. While its disclosure is necessary, e.g., to provide location-based services (LBS), it also facilitates deep insights into the lives of LBS users as well as various attacks on these users. Location privacy threats can be mitigated through privacy regulations such as the General Data Protection Regulation (GDPR), which was introduced recently and harmonises data privacy laws across Europe. While the GDPR is meant to protect users’ privacy, the main problem is that it does not provide explicit guidelines for designers and developers about how to build systems that comply with it. In order to bridge this gap, we systematically analysed the legal text, carried out expert interviews, and ran a nine-week-long take-home study with four developers. We particularly focused on user-facing issues, as these have received little attention compared to technical issues. Our main contributions are a list of aspects from the legal text of the GDPR that can be tackled at the user interface level and a set of guidelines on how to realise this. Our results can help service providers, designers and developers of applications dealing with location information from human users to comply with the GDPR.

Memorizing Algorithm

2010 ◽  
Vol 2 (4) ◽  
pp. 65-86 ◽  
Author(s):  
Quynh Chi Truong ◽  
Anh Tuan Truong ◽  
Tran Khanh Dang
Keyword(s):  
Data Mining ◽  
Service Providers ◽  
Rapid Development ◽  
Adaptive Grid ◽  
Location Based Services ◽  
Location Information ◽  
Data Mining Techniques ◽  
Location Data ◽  
Spatial Grid ◽  
Theoretical Analyses

The rapid development of location-based services, which make use of the location information of the user, presents both opportunities and challenges. Users can benefit from these services; however, they must often disclose their location information, which may lead to privacy problems. In this regard, the authors propose a solution with a memorizing algorithm, using trusted middleware that organizes space in an adaptive grid where it cloaks the user’s location information in an anonymization area before sending it to the service providers. This newly introduced memorizing algorithm calculates on the spatial grid to decrease the overlapped areas as much as possible, which helps conceal users’ locations. This solution protects the user’s privacy while using the service, but also against data mining techniques with respect to their history location data. Experimental results with a user activities map establishes this theoretical analyses as well as the practical value of the proposed solution.

Memorizing Algorithm

Cyber Crime ◽  
2013 ◽  
pp. 600-617
Author(s):  
Quynh Chi Truong ◽  
Anh Tuan Truong ◽  
Tran Khanh Dang
Keyword(s):  
Data Mining ◽  
Service Providers ◽  
Rapid Development ◽  
Adaptive Grid ◽  
Location Based Services ◽  
Location Information ◽  
Data Mining Techniques ◽  
Location Data ◽  
Spatial Grid ◽  
Theoretical Analyses

The rapid development of location-based services, which make use of the location information of the user, presents both opportunities and challenges. Users can benefit from these services; however, they must often disclose their location information, which may lead to privacy problems. In this regard, the authors propose a solution with a memorizing algorithm, using trusted middleware that organizes space in an adaptive grid where it cloaks the user’s location information in an anonymization area before sending it to the service providers. This newly introduced memorizing algorithm calculates on the spatial grid to decrease the overlapped areas as much as possible, which helps conceal users’ locations. This solution protects the user’s privacy while using the service, but also against data mining techniques with respect to their history location data. Experimental results with a user activities map establishes this theoretical analyses as well as the practical value of the proposed solution.

Memorizing Algorithm

2012 ◽  
pp. 242-260
Author(s):  
Quynh Chi Truong ◽  
Anh Tuan Truong ◽  
Tran Khanh Dang
Keyword(s):  
Data Mining ◽  
Service Providers ◽  
Rapid Development ◽  
Adaptive Grid ◽  
Location Based Services ◽  
Location Information ◽  
Data Mining Techniques ◽  
Location Data ◽  
Spatial Grid ◽  
Theoretical Analyses

The rapid development of location-based services, which make use of the location information of the user, presents both opportunities and challenges. Users can benefit from these services; however, they must often disclose their location information, which may lead to privacy problems. In this regard, the authors propose a solution with a memorizing algorithm, using trusted middleware that organizes space in an adaptive grid where it cloaks the user’s location information in an anonymization area before sending it to the service providers. This newly introduced memorizing algorithm calculates on the spatial grid to decrease the overlapped areas as much as possible, which helps conceal users’ locations. This solution protects the user’s privacy while using the service, but also against data mining techniques with respect to their history location data. Experimental results with a user activities map establishes this theoretical analyses as well as the practical value of the proposed solution.

Semantic localization

2017 ◽  
Vol 01 (01) ◽  
pp. 1630010 ◽  
Author(s):  
Shang Ma ◽  
Qiong Liu
Keyword(s):  
Domain Knowledge ◽  
Indoor Localization ◽  
System Modeling ◽  
Location Based Services ◽  
Real Application ◽  
Location Data ◽  
Advantages And Disadvantages ◽  
Personalized Services ◽  
Semantic Localization ◽  
Application Requirements

Improvements in sensor and wireless network enable accurate, automated, instant determination and dissemination of a user’s or objects position. The new enabler of location-based services (LBSs) apart from the current ubiquitous networking infrastructure is the enrichment of the different systems with semantics information, such as time, location, individual capability, preference and more. Such semantically enriched system-modeling aims at developing applications with enhanced functionality and advanced reasoning capabilities. These systems are able to deliver more personalized services to users by domain knowledge with advanced reasoning mechanisms, and provide solutions to problems that were otherwise infeasible. This approach also takes user’s preference and place property into consideration that can be utilized to achieve a comprehensive range of personalized services, such as advertising, recommendations, or polling. This paper provides an overview of indoor localization technologies, popular models for extracting semantics from location data, approaches for associating semantic information and location data, and applications that may be enabled with location semantics. To make the presentation easy to understand, we will use a museum scenario to explain pros and cons of different technologies and models. More specifically, we will first explore users’ needs in a museum scenario. Based on these needs, we will then discuss advantages and disadvantages of using different localization technologies to meet these needs. From these discussions, we can highlight gaps between real application requirements and existing technologies, and point out promising localization research directions. By identifying gaps between various models and real application requirements, we can draw a roadmap for future location semantics research.

scholarly journals A Location Privacy Attack Based on the Location Sharing Mechanism with Erroneous Distance in Geosocial Networks

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 918 ◽  
Author(s):  
Tu-Liang Lin ◽  
Hong-Yi Chang ◽  
Sheng-Lin Li
Keyword(s):  
Location Privacy ◽  
Service Providers ◽  
Dominating Set ◽  
Research Area ◽  
Location Based Services ◽  
Location Information ◽  
Distance Information ◽  
Space Partition ◽  
Location Sharing ◽  
True Location

Geographical social networks (GSN) is an emerging research area. For example, Foursquare, Yelp, and WeChat are all well-known service providers in this field. These applications are also known as location-based services (LBS). Previous studies have suggested that these location-based services may expose user location information. In order to ensure the privacy of the user’s location data, the service provider may provide corresponding protection mechanisms for its applications, including spatial cloaking, fuzzy location information, etc., so that the user’s real location cannot be easily cracked. It has been shown that if the positioning data provided by the user is not accurate enough, it is still difficult for an attacker to obtain the user’s true location. Taking this factor into consideration, our attack method is divided into two stages for the entire attack process: (1) Search stage: cover the area where the targeted user is located with unit discs, and then calculate the minimum dominating set. Use the triangle positioning method to find the minimum precision disc. (2) Inference phase: Considering the existence of errors, an Error-Adjusted Space Partition Attack Algorithm (EASPAA) was proposed during the inference phase. Improved the need for accurate distance information to be able to derive the user’s true location. In this study, we focus on the Location Sharing Mechanism with Maximal Coverage Limit to implement the whole attack. Experimental results show that the proposed method still can accurately infer the user’s real location even when there is an error in the user’s location information.

scholarly journals Location Based Services for Sharing Using Trusted Server

2020 ◽  
pp. 68-73
Keyword(s):  
Social Networks ◽  
Location Privacy ◽  
Location Based Services ◽  
Location Information ◽  
Location Based Service ◽  
Privacy Concerns ◽  
Computational Overhead ◽  
Location Sharing ◽  
Current Location ◽  
Cryptographic Primitive

The main aim of location-sharing is to provide current location information to their designated users. Nowadays, Location Based Service (LBS) has become one of the popular services which are provided by social networks. As LBS activity makes use of the user's identity and current location information, an appropriate path has to be utilized to protect the location privacy. However, as per our knowledge, there is no access to protecting the location sharing with the complete privacy of the location. To consider this issue, we put forward a new cryptographic primitive functional pseudonym for location sharing that make sure privacy of the data. Also, the proposed approach notably reduces the computational overhead of users by delegating part of the computation for location sharing to a server, therefore it is endurable. The primitive can be widely used in many MOSNs to authorize LBS with enhanced privacy and sustainability. As a result, it will contribute to proliferate LBS by eliminating user's privacy concerns.

Enhancing Location Privacy in Location-Based Services

2013 ◽  
pp. 238-250
Author(s):  
Constantinos Delakouridis
Keyword(s):  
Mobile Phones ◽  
Location Privacy ◽  
Service Providers ◽  
Personal Information ◽  
Mobile User ◽  
Location Based Services ◽  
Location Information ◽  
Position Information ◽  
Privacy Requirements ◽  
Privacy Issues

Location-based services are receiving signification attention over the last few years due to the increasing use of mobile devices. At the same time, location privacy is important, since position information is considered personal information. Thus, in order to address this issue, several mechanisms have been proposed protecting the mobile user. In this chapter, the authors present an architecture to shield the location of a mobile user and preserve the anonymity on the service delivery. This architecture relies on un-trusted entities to distribute segments of anonymous location information, and authorizes other entities to combine these portions and derive the actual location of a user. The chapter describes how the architecture takes into account the location privacy requirements, and how it is used by the end users’ devices, e.g., mobile phones, for the dissemination of location information to service providers. Furthermore, it notes privacy issues for further discussion and closes with proposed exercises.

ILSSPP: Intelligent location sharing system with privacy preserving features for smart cities

2021 ◽  
pp. 1-12
Author(s):  
Gokay Saldamli ◽  
Richard Chow ◽  
Hongxia Jin
Keyword(s):  
Service Providers ◽  
Smart Cities ◽  
User Interaction ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Third Party ◽  
Location Information ◽  
Fine Grained ◽  
Location Sharing ◽  
Social Network Structure

Social networking services are increasingly accessed through mobile devices. This trend has prompted services such as Facebook and Google+to incorporate location as a de facto feature of user interaction. At the same time, services based on location such as Foursquare and Shopkick are also growing as smartphone market penetration increases. In fact, this growth is happening despite concerns (growing at a similar pace) about security and third-party use of private location information (e.g., for advertising). Nevertheless, service providers have been unwilling to build truly private systems in which they do not have access to location information. In this paper, we describe an architecture and a trial implementation of a privacy-preserving location sharing system called ILSSPP. The system protects location information from the service provider and yet enables fine grained location-sharing. One main feature of the system is to protect an individual’s social network structure. The pattern of location sharing preferences towards contacts can reveal this structure without any knowledge of the locations themselves. ILSSPP protects locations sharing preferences through protocol unification and masking. ILSSPP has been implemented as a standalone solution, but the technology can also be integrated into location-based services to enhance privacy.

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