Do Identity and Location Data Interrelate? New Affiliations and Privacy Concerns in Social-Driven Sharing

2019 ◽  
pp. 3-16
Author(s):  
Katerina Vgena ◽  
Angeliki Kitsiou ◽  
Christos Kalloniatis ◽  
Dimitris Kavroudakis
Keyword(s):  
Privacy Concerns ◽  
Location Data

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.

Geosurveillance, Location Privacy, and Personalization

2019 ◽  
Vol 38 (4) ◽  
pp. 484-499 ◽  
Author(s):  
Syagnik Banerjee
Keyword(s):  
Data Storage ◽  
Location Privacy ◽  
Data Service ◽  
Policy Makers ◽  
Privacy Concerns ◽  
Digital Footprint ◽  
Location Data ◽  
Legal Standards ◽  
Risk Profiling ◽  
The Rich

As connected consumers expand their digital footprint, firms are legally purchasing location data generated by apps, sold to intermediaries, and cleaned by analytics vendors for personalized targeting, advertising, and risk profiling. Data storage and flow across multiple sectors and states cause increased variability in agency jurisdiction, legal standards, and premise for legal recourse to privacy violations. To better inform industries, policy makers, and consumers in this rapidly changing environment, the author develops a new construct, location privacy, articulating the rich impact of geosurveillance on the consumer. Analysis of studies conducted using car GPS and wearable devices find that data service provider familiarity (known, unknown) and georeferencing style (environment, movement) affect location privacy concerns and the adoption likelihood of personalized driving and health insurance policies underwritten with disclosed location data. The article discusses implications about potential marketer liabilities and regulators’ roles in moderating the market’s concerns regarding geosurveillance.

scholarly journals Lattice Cryptography based Geo-encrypted Contact Tracing for Infection Detection

2021 ◽  
Author(s):  
Mayank Dhiman ◽  
Nitin Gupta ◽  
Ujjawal Gupta ◽  
Yashwant Kumar
Keyword(s):  
World Health ◽  
Contact Tracing ◽  
Infected Person ◽  
Privacy Concerns ◽  
Location Data ◽  
Learning With Errors ◽  
The Government ◽  
Health Organization ◽  
Is Design ◽  
Epidemic Diseases

The world has already witnessed many epidemic diseases in the past years, like H1N1, SARS, and Ebola etc. Now, Covid-19 has also been added to list, which is declared as pandemic by World Health Organization. One of the most commonly used method to tackle the spread of such diseases is using mobile applications to perform contact tracing of the infected person. However, contact tracing applications involve transmitting sensitive location based data of the infected person to the government servers. Therefore, recently this has raised a lot of concerns regarding privacy of the infected persons. This work proposes a light-weight and secure encryption scheme, based on location based encryption which can be used to transfer the location data to the server without compromising its security. The main aim of the work is design an algorithm in such a way that the encrypted transferred data can only be decrypted at the server and in-between data leakage can be prevented. This work proposes to use location based encryption combined with Learning with Errors problems in Lattices, which can provide a solution to privacy concerns in contact tracing, which will even be applicable in the post quantum period.

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 Lattice Cryptography based Geo-encrypted Contact Tracing for Infection Detection

2021 ◽  
Author(s):  
Mayank Dhiman ◽  
Nitin Gupta ◽  
Ujjawal Gupta ◽  
Yashwant Kumar
Keyword(s):  
World Health ◽  
Contact Tracing ◽  
Infected Person ◽  
Privacy Concerns ◽  
Location Data ◽  
Learning With Errors ◽  
The Government ◽  
Health Organization ◽  
Is Design ◽  
Epidemic Diseases

The world has already witnessed many epidemic diseases in the past years, like H1N1, SARS, and Ebola etc. Now, Covid-19 has also been added to list, which is declared as pandemic by World Health Organization. One of the most commonly used method to tackle the spread of such diseases is using mobile applications to perform contact tracing of the infected person. However, contact tracing applications involve transmitting sensitive location based data of the infected person to the government servers. Therefore, recently this has raised a lot of concerns regarding privacy of the infected persons. This work proposes a light-weight and secure encryption scheme, based on location based encryption which can be used to transfer the location data to the server without compromising its security. The main aim of the work is design an algorithm in such a way that the encrypted transferred data can only be decrypted at the server and in-between data leakage can be prevented. This work proposes to use location based encryption combined with Learning with Errors problems in Lattices, which can provide a solution to privacy concerns in contact tracing, which will even be applicable in the post quantum period.

Privacy Concerns Persist, Could Be EHR Hurdle

2006 ◽  
Vol 39 (4) ◽  
pp. 68-69
Author(s):  
NELLIE BRISTOL
Keyword(s):  
Privacy Concerns

Retail Mix Dan Kepuasan Konsumen Minimarket

Liquidity ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 53-62
Author(s):  
Siti Maryama ◽  
Yayat Sujatna
Keyword(s):  
Consumer Satisfaction ◽  
Quantitative Method ◽  
Descriptive Analysis ◽  
T Test ◽  
Primary Data ◽  
Retail Industry ◽  
Location Data ◽  
Store Design ◽  
Customer Services ◽  
The Difference

The purpose of this study is to (1) analyzing the level of retail mix consumer satisfaction; (2) analyze the dominant variable in retail mix consumer satisfaction; (3) analyze the difference of retail mix consumer satisfaction performed. The observed of the retail industry is Alfamidi and Indomaret. The study was designed into a descriptive-quantitative method. The source of primary data obtained from the questionnaire of 100 respondents. The formulating variable of retail mix includes: merchandise assortments, pricing, customer services Store design and display, communication mix, and location. Data analyze by using descriptive, analysis of factors, and t-test. The result confirmed that the level of retail mix consumer satisfaction in both industry is relatively similar. However, it can be stated that the respondents were more satisfied to Indomaret compared with Alfamart.

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