Two-Stage Privacy-Preserving Mechanism for a Crowdsensing-Based VSN

Li, Hui; Liu, Dan; Sun, Gang; Zhang, Ming; Du, Xuehui; Han, Zuijiao

doi:10.1109/access.2018.2854236

Cited by 12 publications

(4 citation statements)

References 41 publications

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“…Studies have also considered these social communications from the perspective of privacy. For example, Li et al 17 provide a way to protect privacy by using social communications in mobile crowdsourcing networks and have developed solutions for identity management. But the presented method is specifically designed for Vehicular Social Networks.…”

Section: Related Workmentioning

confidence: 99%

A privacy‐preserving mechanism for social mobile crowdsensing using game theory

Esmaeilyfard

Esmaili

2022

Trans Emerging Tel Tech

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Smartphones and mobile networks have created a new paradigm called mobile crowdsensing for data gathering and processing about a large-scale phenomenon. This paradigm's development allows untrustworthy people to gather large amounts of information over time from the reported events. In this regard, mobile crowdsensing increases the possibility of violating users' privacy. Recently, social communication has added potential capabilities to mobile crowdsourcing environments. Based on these social communications, this article presents an analysis of user's interactions for privacy-preserving using a signaling game with a dynamic approach and incomplete information. First, the analysis identifies the pure-strategy profiles and mixed-strategy profiles and the user's best strategy for accepting access requests in a single time slot. This analysis is then extended into a dynamic multistage game. In this analysis, users' beliefs about the violation of their privacy are analyzed and updated at every stage. As a result, the best response from users will be determined. Following this analysis, a mechanism is presented for privacy-preserving in social mobile crowdsensing. The experimental results have also indicated the success of the proposed method in dealing with different types of user interaction.

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Section: Related Workmentioning

confidence: 99%

A privacy‐preserving mechanism for social mobile crowdsensing using game theory

Esmaeilyfard

Esmaili

2022

Trans Emerging Tel Tech

View full text Add to dashboard Cite

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“…When there are few neighbors around a user, this user is unable to cannot hide their identities effectively. Accordingly, in order to reduce the influence of the number of adjacent nodes on the degree of user privacy protection, Li et al [38] devised a novel identity management method. Considering a target user, when other users and the target user are in the same group, they exchange pseudonym information between each other.…”

Section: A Location Privacy Protection Based On User Attribute Informentioning

confidence: 99%

“…Mixed areas such as these are generally set up at large intersections or shopping malls. Li et al [38] applied crowdsourcing awareness technology to SIoV and designed a two-stage privacy-preserving (TSPP) suppression algorithm to avoid the leakage of user private information. While driving vehicle, some data needs to be uploaded regularly, and there is a certain probability at a certain location that the system will suppress the uploading of certain sensor data.…”

Section: ) Privacy Protection Based On Driving Trajectorymentioning

confidence: 99%

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A Survey of Location Privacy Preservation in Social Internet of Vehicles

et al. 2020

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Social Internet of Vehicles (SIoV) is an emerging complex network where the features of Social Networks are applied to the SIoV system. User location data forms the basis for the implementation of SIoV functions. However, this type of data contains a large amount of user personal information, which may cause privacy leakage if it is stolen. Protecting the privacy of the user location can eliminate concerns about the leakage of user personal privacy data, increase users' viscosity, and help to contribute to the improvement of the SIoV system. This paper systematically analyzes the location privacy protection technology utilized in recent years in the field of SIoV, proposes three types of user data location privacy protection technology, and evaluates the performance of these technologies. We further present some potential future research directions for location privacy protection technology through the analysis and summary of existing work.

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Blockchain Meets VANET: An Architecture for Identity and Location Privacy Protection in VANET

Pei

Liu

et al. 2019

Peer-to-Peer Netw. Appl.

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Two-Stage Privacy-Preserving Mechanism for a Crowdsensing-Based VSN

Cited by 12 publications

References 41 publications

A privacy‐preserving mechanism for social mobile crowdsensing using game theory

A privacy‐preserving mechanism for social mobile crowdsensing using game theory

A Survey of Location Privacy Preservation in Social Internet of Vehicles

Blockchain Meets VANET: An Architecture for Identity and Location Privacy Protection in VANET

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