Evolution of Privacy Preservation Models in Location-Based Services

2020 ◽  
Vol 5 (3) ◽  
pp. 82-92
Author(s):  
A B Manju ◽  
Sumathy Subramanian
Keyword(s):  
Privacy Preservation ◽  
Location Based Services

scholarly journals Decentralized collaborative TTP free approach for privacy preservation in location based services

2019 ◽  
Vol 9 (6) ◽  
pp. 5376
Author(s):  
Ajaysinh Devendrasinh Rathod ◽  
Saurabh Shah ◽  
Vivaksha J. Jariwala
Keyword(s):  
Privacy Preservation ◽  
Location Privacy ◽  
Emergency Services ◽  
Personal Information ◽  
Personal Digital Assistant ◽  
Minimum Cost ◽  
Location Based Services ◽  
Third Party ◽  
Trusted Third Party ◽  
Recent Trends

In recent trends, growth of location based services have been increased due to the large usage of cell phones, personal digital assistant and other devices like location based navigation, emergency services, location based social networking, location based advertisement, etc. Users are provided with important information based on location to the service provider that results the compromise with their personal information like user’s identity, location privacy etc. To achieve location privacy of the user, cryptographic technique is one of the best technique which gives assurance. Location based services are classified as Trusted Third Party (TTP) & without Trusted Third Party that uses cryptographic approaches. TTP free is one of the prominent approach in which it uses peer-to-peer model. In this approach, important users mutually connect with each other to form a network to work without the use of any person/server. There are many existing approaches in literature for privacy preserving location based services, but their solutions are at high cost or not supporting scalability.  In this paper, our aim is to propose an approach along with algorithms that will help the location based services (LBS) users to provide location privacy with minimum cost and improve scalability.

scholarly journals Privacy Preservation in Location-Based Services: A Novel Metric and Attack Model

2020 ◽  
pp. 1-1 ◽  
Author(s):  
Sina Shaham ◽  
Ming Ding ◽  
Bo Liu ◽  
Shuping Dang ◽  
Zihuai Lin ◽  
...  
Keyword(s):  
Privacy Preservation ◽  
Location Based Services ◽  
Attack Model

scholarly journals Accountable Outsourcing Location-Based Services With Privacy Preservation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 117258-117273 ◽  
Author(s):  
Zhaoman Liu ◽  
Lei Wu ◽  
Junming Ke ◽  
Wenlei Qu ◽  
Wei Wang ◽  
...  
Keyword(s):  
Privacy Preservation ◽  
Location Based Services

scholarly journals Enabling Location Privacy Preservation in MANETs Based on Distance, Angle, and Spatial Cloaking

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 458
Author(s):  
Nanlan Jiang ◽  
Sai Yang ◽  
Pingping Xu
Keyword(s):  
Privacy Preservation ◽  
Location Privacy ◽  
Differential Privacy ◽  
Geographic Routing ◽  
Base Station ◽  
Wireless Channel ◽  
Location Based Services ◽  
Location Information ◽  
Communication Overhead ◽  
Spatial Cloaking

Preserving the location privacy of users in Mobile Ad hoc Networks (MANETs) is a significant challenge for location information. Most of the conventional Location Privacy Preservation (LPP) methods protect the privacy of the user while sacrificing the capability of retrieval on the server-side, that is, legitimate devices except the user itself cannot retrieve the location in most cases. On the other hand, applications such as geographic routing and location verification require the retrievability of locations on the access point, the base station, or a trusted server. Besides, with the development of networking technology such as caching technology, it is expected that more and more distributed location-based services will be deployed, which results in the risk of leaking location information in the wireless channel. Therefore, preserving location privacy in wireless channels without losing the retrievability of the real location is essential. In this paper, by focusing on the wireless channel, we propose a novel LPP enabled by distance (ranging result), angle, and the idea of spatial cloaking (DSC-LPP) to preserve location privacy in MANETs. DSC-LPP runs without the trusted third party nor the traditional cryptography tools in the line-of-sight environment, and it is suitable for MANETs such as the Internet of Things, even when the communication and computation capabilities of users are limited. Qualitative evaluation indicates that DSC-LPP can reduce the communication overhead when compared with k-anonymity, and the computation overhead of DSC-LPP is limited when compared with conventional cryptography. Meanwhile, the retrievability of DSC-LPP is higher than that of k-anonymity and differential privacy. Simulation results show that with the proper design of spatial divisions and parameters, other legitimate devices in a MANET can correctly retrieve the location of users with a high probability when adopting DSC-LPP.

scholarly journals Privacy preservation in mobile social networks

2019 ◽  
Author(s):  
◽  
Douglas Steiert
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Privacy Preservation ◽  
Location Based Services ◽  
Mobile Social Networks ◽  
Privacy Concerns ◽  
Average Person ◽  
Effectiveness And Efficiency ◽  
Privacy Breaches

In this day and age with the prevalence of smartphones, networking has evolved in an intricate and complex way. With the help of a technology-driven society, the term "social networking" was created and came to mean using media platforms such as Myspace, Facebook, and Twitter to connect and interact with friends, family, or even complete strangers. Websites are created and put online each day, with many of them possessing hidden threats that the average person does not think about. A key feature that was created for vast amount of utility was the use of location-based services, where many websites inform their users that the website will be using the users' locations to enhance the functionality. However, still far too many websites do not inform their users that they may be tracked, or to what degree. In a similar juxtaposed scenario, the evolution of these social networks has allowed countless people to share photos with others online. While this seems harmless at face-value, there may be times in which people share photos of friends or other non-consenting individuals who do not want that picture viewable to anyone at the photo owner's control. There exists a lack of privacy controls for users to precisely de fine how they wish websites to use their location information, and for how others may share images of them online. This dissertation introduces two models that help mitigate these privacy concerns for social network users. MoveWithMe is an Android and iOS application which creates decoys that move locations along with the user in a consistent and semantically secure way. REMIND is the second model that performs rich probability calculations to determine which friends in a social network may pose a risk for privacy breaches when sharing images. Both models have undergone extensive testing to demonstrate their effectiveness and efficiency.

K-anonymity scheme for privacy preservation in location-based services on IoT environment

2021 ◽  
Vol 15 (3) ◽  
pp. 340
Author(s):  
Ayan Kumar Das ◽  
Ayesha Tabassum ◽  
Sayema Sadaf ◽  
Ditipriya Sinha
Keyword(s):  
Privacy Preservation ◽  
Location Based Services

Privacy Preservation in Location-Based Services

2018 ◽  
Vol 56 (3) ◽  
pp. 134-140 ◽  
Author(s):  
Shengling Wang ◽  
Qin Hu ◽  
Yunchuan Sun ◽  
Jianhui Huang
Keyword(s):  
Privacy Preservation ◽  
Location Based Services

Multidimensional privacy preservation in location-based services

2019 ◽  
Vol 93 ◽  
pp. 312-326 ◽  
Author(s):  
Tao Peng ◽  
Qin Liu ◽  
Guojun Wang ◽  
Yang Xiang ◽  
Shuhong Chen
Keyword(s):  
Privacy Preservation ◽  
Location Based Services
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