scholarly journals A Location Privacy Preservation Method Based on Dummy Locations in Internet of Vehicles

2021 ◽  
Vol 11 (10) ◽  
pp. 4594
Author(s):  
Xianyun Xu ◽  
Huifang Chen ◽  
Lei Xie
Keyword(s):  
Privacy Preservation ◽  
Location Privacy ◽  
Third Party ◽  
Effective Distance ◽  
Internet Of Vehicles ◽  
Location Selection ◽  
Point Of Interest ◽  
Preservation Method ◽  
Vehicle Location ◽  
Candidate Location

During the procedure, a location-based service (LBS) query, the real location provided by the vehicle user may results in the disclosure of vehicle location privacy. Moreover, the point of interest retrieval service requires high accuracy of location information. However, some privacy preservation methods based on anonymity or obfuscation will affect the service quality. Hence, we study the location privacy-preserving method based on dummy locations in this paper. We propose a vehicle location privacy-preservation method based on dummy locations under road restriction in Internet of vehicles (IoV). In order to improve the validity of selected dummy locations under road restriction, entropy is used to represent the degree of anonymity, and the effective distance is introduced to represent the characteristics of location distribution. We present a dummy location selection algorithm to maximize the anonymous entropy and the effective distance of candidate location set consisting of vehicle user’s location and dummy locations, which ensures the uncertainty and dispersion of selected dummy locations. The proposed location privacy-preservation method does not need a trustable third-party server, and it protects the location privacy of vehicles as well as guaranteeing the LBS quality. The performance analysis and simulation results show that the proposed location privacy-preservation method can improve the validity of dummy locations and enhance the preservation of location privacy compared with other methods based on dummy locations.

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 KLPPS: A k-Anonymous Location Privacy Protection Scheme via Dummies and Stackelberg Game

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Dongdong Yang ◽  
Baopeng Ye ◽  
Wenyin Zhang ◽  
Huiyu Zhou ◽  
Xiaobin Qian
Keyword(s):  
Service Quality ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Location Privacy ◽  
Stackelberg Game ◽  
Single Point ◽  
Third Party ◽  
Protection Scheme ◽  
Inference Attacks ◽  
Location Privacy Protection

Protecting location privacy has become an irreversible trend; some problems also come such as system structures adopted by location privacy protection schemes suffer from single point of failure or the mobile device performance bottlenecks, and these schemes cannot resist single-point attacks and inference attacks and achieve a tradeoff between privacy level and service quality. To solve these problems, we propose a k-anonymous location privacy protection scheme via dummies and Stackelberg game. First, we analyze the merits and drawbacks of the existing location privacy preservation system architecture and propose a semitrusted third party-based location privacy preservation architecture. Next, taking into account both location semantic diversity, physical dispersion, and query probability, etc., we design a dummy location selection algorithm based on location semantics and physical distance, which can protect users’ privacy against single-point attack. And then, we propose a location anonymous optimization method based on Stackelberg game to improve the algorithm. Specifically, we formalize the mutual optimization of user-adversary objectives by using the framework of Stackelberg game to find an optimal dummy location set. The optimal dummy location set can resist single-point attacks and inference attacks while effectively balancing service quality and location privacy. Finally, we provide exhaustive simulation evaluation for the proposed scheme compared with existing schemes in multiple aspects, and the results show that the proposed scheme can effectively resist the single-point attack and inference attack while balancing the service quality and location privacy.

scholarly journals A Survey of Location Privacy Preservation in Social Internet of Vehicles

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 201966-201984
Author(s):  
Xiaofan Jia ◽  
Ling Xing ◽  
Jianping Gao ◽  
Honghai Wu
Keyword(s):  
Privacy Preservation ◽  
Location Privacy ◽  
Internet Of Vehicles

scholarly journals Virtual Pseudonym-Changing and Dynamic Grouping Policy for Privacy Preservation in VANETs

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 3077
Author(s):  
Ikram Ullah ◽  
Munam Ali Shah ◽  
Abid Khan ◽  
Carsten Maple ◽  
Abdul Waheed
Keyword(s):  
Communication Networks ◽  
Privacy Preservation ◽  
Location Privacy ◽  
Research Work ◽  
Silent Period ◽  
Research Literature ◽  
Traffic Density ◽  
Message Content ◽  
Vehicular Communication ◽  
Vehicle Location

Location privacy is a critical problem in the vehicular communication networks. Vehicles broadcast their road status information to other entities in the network through beacon messages to inform other entities in the network. The beacon message content consists of the vehicle ID, speed, direction, position, and other information. An adversary could use vehicle identity and positioning information to determine vehicle driver behavior and identity at different visited location spots. A pseudonym can be used instead of the vehicle ID to help in the vehicle location privacy. These pseudonyms should be changed in appropriate way to produce uncertainty for any adversary attempting to identify a vehicle at different locations. In the existing research literature, pseudonyms are changed during silent mode between neighbors. However, the use of a short silent period and the visibility of pseudonyms of direct neighbors provides a mechanism for an adversary to determine the identity of a target vehicle at specific locations. Moreover, privacy is provided to the driver, only within the RSU range; outside it, there is no privacy protection. In this research, we address the problem of location privacy in a highway scenario, where vehicles are traveling at high speeds with diverse traffic density. We propose a Dynamic Grouping and Virtual Pseudonym-Changing (DGVP) scheme for vehicle location privacy. Dynamic groups are formed based on similar status vehicles and cooperatively change pseudonyms. In the case of low traffic density, we use a virtual pseudonym update process. We formally present the model and specify the scheme through High-Level Petri Nets (HLPN). The simulation results indicate that the proposed method improves the anonymity set size and entropy, provides lower traceability, reduces impact on vehicular network applications, and has lower computation cost compared to existing research work.

Subspace k-anonymity algorithm for location-privacy preservation based on locality-sensitive hashing

2019 ◽  
Vol 23 (5) ◽  
pp. 1167-1185
Author(s):  
Xiaohan Wang ◽  
Yonglong Luo ◽  
Shiyang Liu ◽  
Taochun Wang ◽  
Huihui Han
Keyword(s):  
Privacy Preservation ◽  
Location Privacy ◽  
Locality Sensitive Hashing

scholarly journals A K-Anonymity Based Schema for Location Privacy Preservation

2019 ◽  
Vol 4 (2) ◽  
pp. 156-167 ◽  
Author(s):  
Fan Fei ◽  
Shu Li ◽  
Haipeng Dai ◽  
Chunhua Hu ◽  
Wanchun Dou ◽  
...  
Keyword(s):  
Privacy Preservation ◽  
Location Privacy
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