Fine-Grained Privacy-Preserving Spatiotemporal Matching in Mobile Social Networks

2015 ◽  
Author(s):  
Xiuguang Li ◽  
Kai Yang ◽  
Hui Li
Keyword(s):  
Social Networks ◽  
Privacy Preserving ◽  
Mobile Social Networks ◽  
Fine Grained

Privacy-Preserving Fine-Grained Data Retrieval Schemes for Mobile Social Networks

2019 ◽  
Vol 16 (5) ◽  
pp. 871-884 ◽  
Author(s):  
Mohamed Mahmoud ◽  
Khaled Rabieh ◽  
Ahmed Sherif ◽  
Enahoro Oriero ◽  
Muhammad Ismail ◽  
...  
Keyword(s):  
Social Networks ◽  
Data Retrieval ◽  
Privacy Preserving ◽  
Mobile Social Networks ◽  
Fine Grained

scholarly journals Privacy-Enhancing k-Nearest Neighbors Search over Mobile Social Networks

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 3994
Author(s):  
Yuxi Li ◽  
Fucai Zhou ◽  
Yue Ge ◽  
Zifeng Xu
Keyword(s):  
Social Networks ◽  
Access Control ◽  
Location Privacy ◽  
Nearest Neighbors ◽  
Search Pattern ◽  
Broadcast Encryption ◽  
Mobile Social Networks ◽  
K Nearest Neighbors ◽  
Fine Grained ◽  
Server Architecture

Focusing on the diversified demands of location privacy in mobile social networks (MSNs), we propose a privacy-enhancing k-nearest neighbors search scheme over MSNs. First, we construct a dual-server architecture that incorporates location privacy and fine-grained access control. Under the above architecture, we design a lightweight location encryption algorithm to achieve a minimal cost to the user. We also propose a location re-encryption protocol and an encrypted location search protocol based on secure multi-party computation and homomorphic encryption mechanism, which achieve accurate and secure k-nearest friends retrieval. Moreover, to satisfy fine-grained access control requirements, we propose a dynamic friends management mechanism based on public-key broadcast encryption. It enables users to grant/revoke others’ search right without updating their friends’ keys, realizing constant-time authentication. Security analysis shows that the proposed scheme satisfies adaptive L-semantic security and revocation security under a random oracle model. In terms of performance, compared with the related works with single server architecture, the proposed scheme reduces the leakage of the location information, search pattern and the user–server communication cost. Our results show that a decentralized and end-to-end encrypted k-nearest neighbors search over MSNs is not only possible in theory, but also feasible in real-world MSNs collaboration deployment with resource-constrained mobile devices and highly iterative location update demands.

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