scholarly journals Location Privacy Protection in Distributed IoT Environments Based on Dynamic Sensor Node Clustering

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 3022 ◽  
Author(s):  
Konstantinos Dimitriou ◽  
Ioanna Roussaki
Keyword(s):  
Location Privacy ◽  
Clustering Algorithm ◽  
Data Dissemination ◽  
Location Information ◽  
Dynamic Clustering ◽  
Sensitive Data ◽  
Mobile Objects ◽  
Current Location ◽  
Series Of Experiments ◽  
Location Privacy Protection

One of the most significant challenges in Internet of Things (IoT) environments is the protection of privacy. Failing to guarantee the privacy of sensitive data collected and shared over IoT infrastructures is a critical barrier that delays the wide penetration of IoT technologies in several user-centric application domains. Location information is the most common dynamic information monitored and lies among the most sensitive ones from a privacy perspective. This article introduces a novel mechanism that aims to protect the privacy of location information across Data Centric Sensor Networks (DCSNs) that monitor the location of mobile objects in IoT systems. The respective data dissemination protocols proposed enhance the security of DCSNs rendering them less vulnerable to intruders interested in obtaining the location information monitored. In this respect, a dynamic clustering algorithm is that clusters the DCSN nodes not only based on the network topology, but also considering the current location of the objects monitored. The proposed techniques do not focus on the prevention of attacks, but on enhancing the privacy of sensitive location information once IoT nodes have been compromised. They have been extensively assessed via series of experiments conducted over the IoT infrastructure of FIT IoT-LAB and the respective evaluation results indicate that the dynamic clustering algorithm proposed significantly outperforms existing solutions focusing on enhancing the privacy of location information in IoT.

scholarly journals Nonexposure Accurate LocationK-Anonymity Algorithm in LBS

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Jinying Jia ◽  
Fengli Zhang
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
Location Based Services ◽  
Experimental Results ◽  
Location Information ◽  
User Privacy ◽  
Spatial Region ◽  
Exact Location ◽  
Current Location ◽  
Location Privacy Protection

This paper tackles location privacy protection in current location-based services (LBS) where mobile users have to report their exact location information to an LBS provider in order to obtain their desired services. Location cloaking has been proposed and well studied to protect user privacy. It blurs the user’s accurate coordinate and replaces it with a well-shaped cloaked region. However, to obtain such an anonymous spatial region (ASR), nearly all existent cloaking algorithms require knowing the accurate locations of all users. Therefore, location cloaking without exposing the user’s accurate location to any party is urgently needed. In this paper, we present such two nonexposure accurate location cloaking algorithms. They are designed forK-anonymity, and cloaking is performed based on the identifications (IDs) of the grid areas which were reported by all the users, instead of directly on their accurate coordinates. Experimental results show that our algorithms are more secure than the existent cloaking algorithms, need not have all the users reporting their locations all the time, and can generate smaller ASR.

scholarly journals Location Privacy Protection Scheme for LBS in IoT

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Hongtao Li ◽  
Xingsi Xue ◽  
Zhiying Li ◽  
Long Li ◽  
Jinbo Xiong
Keyword(s):  
Voronoi Diagram ◽  
Privacy Protection ◽  
Location Privacy ◽  
Location Information ◽  
Protection Scheme ◽  
Server Side ◽  
Location Data ◽  
Location Privacy Protection ◽  
Client Side ◽  
Grid Division

The widespread use of Internet of Things (IoT) technology has promoted location-based service (LBS) applications. Users can enjoy various conveniences brought by LBS by providing location information to LBS. However, it also brings potential privacy threats to location information. Location data that contains private information is often transmitted among IoT networks in LBS, and such privacy information should be protected. In order to solve the problem of location privacy leakage in LBS, a location privacy protection scheme based on k -anonymity is proposed in this paper, in which the Geohash coding model and Voronoi graph are used as grid division principles. We adopt the client-server-to-user (CS2U) model to protect the user’s location data on the client side and the server side, respectively. On the client side, the Geohash algorithm is proposed, which converts the user’s location coordinates into a Geohash code of the corresponding length. On the server side, the Geohash code generated by the user is inserted into the prefix tree, the prefix tree is used to find the nearest neighbors according to the characteristics of the coded similar prefixes, and the Voronoi diagram is used to divide the area units to complete the pruning. Then, using the Geohash coding model and the Voronoi diagram grid division principle, the G-V anonymity algorithm is proposed to find k neighbors in an anonymous area so that the user’s location data meets the k -anonymity requirement in the area unit, thereby achieving anonymity protection of location privacy. Theoretical analysis and experimental results show that our method is effective in terms of privacy and data quality while reducing the time of data anonymity.

A Group Leader Location Hiding Technique for VANETs

2017 ◽  
Vol 8 (3) ◽  
pp. 67-80
Author(s):  
Shaker Aljallad ◽  
Raad S. Al-Qassas ◽  
Malik Qasaimeh
Keyword(s):  
Privacy Protection ◽  
Ad Hoc Network ◽  
Traffic Management ◽  
Location Privacy ◽  
Ad Hoc ◽  
Communication Technologies ◽  
Group Leader ◽  
Location Information ◽  
Critical Requirement ◽  
Location Privacy Protection

Vehicular ad hoc network (VANET) is one of the most promising and emerging communication technologies that could definitely lead to significant improvements in the traffic management and safety. Location privacy is a critical requirement in VANET, since location information may be shared between vehicles to support the VANET applications. Therefore, it is crucial to protect the location of users. In this paper, we propose a location privacy protection technique that utilises the shadow concept and takes into consideration the reliability in protecting the group leader location, which would basically provide the needed anonymity and protection for the location information targeted by global adversaries. The performance of the proposed technique has been investigated through simulation and compared against the well-known AOSA technique. The results from extensive simulations have shown that the proposed technique enhances the anonymity of the group leader vehicle by reducing the time that the global adversaries can use in collecting 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.

Improvement of K-Anonymity Location Privacy Protection Algorithm Based on Hierarchy Clustering

2014 ◽  
Vol 599-601 ◽  
pp. 1553-1557 ◽  
Author(s):  
Zhi Qiang He ◽  
Gang Chen
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
Clustering Algorithm ◽  
Continuous Queries ◽  
Security Level ◽  
Location Based Service ◽  
K Value ◽  
Location Privacy Protection

The k anonymity was one of the first algorithms applied for privacy protection in location-based service(LBS).The k anonymity exhibits its disadvantages gradually, such as being easily attacked by continuous queries attacking algorithm, the larger k value for higher security level lead to more pointless cost of bandwidth and load of LBS server. This article analyzes the causes of the problems, and proposes a new idea based on clustering algorithm to improve the k anonymity algorithm.

scholarly journals Location-Privacy Leakage and Integrated Solutions for 5G Cellular Networks and Beyond

Sensors ◽  
2021 ◽  
Vol 21 (15) ◽  
pp. 5176
Author(s):  
Stefano Tomasin ◽  
Marco Centenaro ◽  
Gonzalo Seco-Granados ◽  
Stefan Roth ◽  
Aydin Sezgin
Keyword(s):  
Cellular Networks ◽  
Mobile Networks ◽  
Location Privacy ◽  
Service Providers ◽  
Information Leakage ◽  
Location Information ◽  
Sensitive Data ◽  
Privacy Leakage ◽  
Improper Use ◽  
User Location

The 5g of cellular networks improves the precision of user localization and provides the means to disclose location information to ott service providers. The nwdaf can further elaborate this information at an aggregated level using artificial intelligence techniques. These powerful features may lead to the improper use of user location information by mno and ott service providers. Moreover, vulnerabilities at various layers may also leak user location information to eavesdroppers. Hence, the privacy of users is likely at risk, as location is part of their sensitive data. In this paper, we first go through the evolution of localization in cellular networks and investigate their effects on location privacy. Then, we propose a location-privacy-preserving integrated solution comprising virtual private mobile networks, an independent authentication and billing authority, and functions to protect wireless signals against location information leakage. Moreover, we advocate the continuous and detailed control of localization services by the user.

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.

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