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 Privacy Preserving Spatio-Temporal Databases Based on k-Anonymity

2020 ◽  
Vol 3 (SI1) ◽  
pp. SI82-SI94
Author(s):  
Anh Tuan Truong
Keyword(s):  
Data Mining ◽  
Privacy Protection ◽  
Location Privacy ◽  
Location Based Services ◽  
Sensitive Information ◽  
User Privacy ◽  
Location Data ◽  
Related Information ◽  
Spatio Temporal ◽  
Location Privacy Protection

The development of location-based services and mobile devices has lead to an increase in the location data. Through the data mining process, some valuable information can be discovered from location data. In the other words, an attacker may also extract some private (sensitive) information of the user and this may make threats against the user privacy. Therefore, location privacy protection becomes an important requirement to the success in the development of location-based services. In this paper, we propose a grid-based approach as well as an algorithm to guarantee k-anonymity, a well-known privacy protection approach, in a location database. The proposed approach considers only the information that has significance for the data mining process while ignoring the un-related information. The experiment results show the effectiveness of the proposed approach in comparison with the literature ones.

scholarly journals A Novel Location Privacy-Preserving Approach Based on Blockchain

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3519 ◽  
Author(s):  
Ying Qiu ◽  
Yi Liu ◽  
Xuan Li ◽  
Jiahui Chen
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
User Participation ◽  
Location Based Services ◽  
Third Party ◽  
User Privacy ◽  
Protection Method ◽  
Location Privacy Protection ◽  
Reward Mechanism

Location-based services (LBS) bring convenience to people’s lives but are also accompanied with privacy leakages. To protect the privacy of LBS users, many location privacy protection algorithms were proposed. However, these algorithms often have difficulty to maintain a balance between service quality and user privacy. In this paper, we first overview the shortcomings of the existing two privacy protection architectures and privacy protection technologies, then we propose a location privacy protection method based on blockchain. Our method satisfies the principle of k-anonymity privacy protection and does not need the help of trusted third-party anonymizing servers. The combination of multiple private blockchains can disperse the user’s transaction records, which can provide users with stronger location privacy protection and will not reduce the quality of service. We also propose a reward mechanism to encourage user participation. Finally, we implement our approach in the Remix blockchain to show the efficiency, which further indicates the potential application prospect for the distributed network environment.

scholarly journals Location Privacy Protection Systems in Presence of Service Quality and Energy Constraints

Information ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 121
Author(s):  
Mulugeta Kassaw Tefera ◽  
Xiaolong Yang
Keyword(s):  
Service Quality ◽  
Privacy Protection ◽  
Location Privacy ◽  
Resource Consumption ◽  
Location Based Services ◽  
Design Strategies ◽  
Energy Constraints ◽  
Location Obfuscation ◽  
Evaluation Mechanism ◽  
Location Privacy Protection

The wide-ranging application of location-based services (LBSs) through the use of mobile devices and wireless networks has brought about many critical privacy challenges. To preserve the location privacy of users, most existing location privacy-preserving mechanisms (LPPMs) modify their real locations associated with different pseudonyms, which come at a cost either in terms of resource consumption or quality of service, or both. However, we observed that the effect of resource consumption has not been discussed in existing studies. In this paper, we present the user-centric LPPMs against location inference attacks under the consideration of both service quality and energy constraints. Moreover, we modeled the precision-based and dummy-based mechanisms in the context of an existing LPPM framework, and also extended the linear program solutions applicable to them. This study allowed us to specify the LPPMs that decreased the precision of exposed locations or generated dummy locations of the users. Based on this, we evaluated the privacy protection effects of optimal location obfuscation function against an adversary's inference attack function using real mobility datasets. The results indicate that dummy-based mechanisms provide better achievable location privacy under a given combination of service quality and energy constraints, and once a certain level of privacy is reached, both the precision-based and dummy-based mechanisms only perturb the exposed locations. The evaluation results also contribute to a better understanding for the LPPM design strategies and evaluation mechanism as far as the system resource utilization and service quality requirements are concerned.

scholarly journals An Efficient and Privacy-Preserving Multiuser Cloud-Based LBS Query Scheme

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Lu Ou ◽  
Hui Yin ◽  
Zheng Qin ◽  
Sheng Xiao ◽  
Guangyi Yang ◽  
...  
Keyword(s):  
Location Privacy ◽  
Security Analysis ◽  
Privacy Preserving ◽  
Location Based Services ◽  
Third Party ◽  
Location Information ◽  
User Privacy ◽  
User Revocation ◽  
And Performance ◽  
Cloud Infrastructures

Location-based services (LBSs) are increasingly popular in today’s society. People reveal their location information to LBS providers to obtain personalized services such as map directions, restaurant recommendations, and taxi reservations. Usually, LBS providers offer user privacy protection statement to assure users that their private location information would not be given away. However, many LBSs run on third-party cloud infrastructures. It is challenging to guarantee user location privacy against curious cloud operators while still permitting users to query their own location information data. In this paper, we propose an efficient privacy-preserving cloud-based LBS query scheme for the multiuser setting. We encrypt LBS data and LBS queries with a hybrid encryption mechanism, which can efficiently implement privacy-preserving search over encrypted LBS data and is very suitable for the multiuser setting with secure and effective user enrollment and user revocation. This paper contains security analysis and performance experiments to demonstrate the privacy-preserving properties and efficiency of our proposed scheme.

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.

scholarly journals QBPP: Quality of services–based location privacy protection method for location-based services in cloud-enabled Internet of vehicles

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771984149
Author(s):  
Ji-ming Chen ◽  
Ting-ting Li ◽  
Liang-jun Wang
Keyword(s):  
Privacy Protection ◽  
Location Privacy ◽  
Virtual Machines ◽  
Location Based Services ◽  
Security Requirements ◽  
Quality Of Services ◽  
Internet Of Vehicles ◽  
Address Data ◽  
Location Privacy Protection

Location-based services has been widely applied in cloud-enabled Internet of vehicles. Within these services, location privacy issues have captured significant attention. Vehicles use the technology of anonymity to implement occultation, the location is not revealed. In this process, large-scale data transmissions can reduce the quality of services. In order to ensure location privacy and high-quality services, the cloud manager customizes virtual machines for vehicles to support location-based services according to the vehicles’ demands. To achieve better performance, this article presents a conditional anonymity method that does not use bilinear pairings to address the problem of privacy disclosure by using discrete logarithm problem and Diffie–Hellman problem. Moreover, asymmetric key algorithms are used in the Internet of vehicles environment to reduce the cost. To guarantee secure data transmission in Internet of vehicles, the batch validation technique is used to address data integrity. Our theoretical security analysis and experiments show that the proposed scheme is secure in compared attack models, such as impersonation attacks, replay attacks, the man-in-the-middle attacks, and so on. Our proposed scheme ensures the security requirements such as message authentication, location privacy protection, and traceability, while lowering transmission and computation cost.

scholarly journals A Novel Method for Location Privacy Protection in LBS Applications

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Dan Lu ◽  
Qilong Han ◽  
Kejia Zhang ◽  
Haitao Zhang ◽  
Bisma Gull
Keyword(s):  
Service Quality ◽  
Privacy Protection ◽  
Location Privacy ◽  
Random Noise ◽  
Location Based Services ◽  
Daily Lives ◽  
Mobile Networking ◽  
Novel Method ◽  
Location Privacy Protection

Location-based services have become a mainstream in people’s daily lives due to continuous innovations in the field of mobile networking and GPS technologies. Recently they have advanced into a hot topic to which the majority of researchers pay close attention about how to enjoy them while safeguarding the location privacy of mobile users. Existing works involve the injection of random noise that cannot pledge the quality of service. Herein this manuscript, we propose a novel location privacy protection model based on the loss of service quality. This model allows the user to express his/her requirement of service quality by specifying the maximum service quality loss Lmax, which is the user’s tolerance. Lmax can be set to 0. Our comprehensive experimental evaluation using a real-world dataset demonstrates that our modus outdoes other state-of-the-art approaches.

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