scholarly journals Fair Secure Computation with Reputation Assumptions in the Mobile Social Networks

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yilei Wang ◽  
Chuan Zhao ◽  
Qiuliang Xu ◽  
Zhihua Zheng ◽  
Zhenhua Chen ◽  
...  
Keyword(s):  
Social Networks ◽  
Mobile Devices ◽  
Rapid Development ◽  
File Sharing ◽  
Secure Computation ◽  
Mobile Social Networks ◽  
Wireless Technologies ◽  
Impossible Task

With the rapid development of mobile devices and wireless technologies, mobile social networks become increasingly available. People can implement many applications on the basis of mobile social networks. Secure computation, like exchanging information and file sharing, is one of such applications. Fairness in secure computation, which means that either all parties implement the application or none of them does, is deemed as an impossible task in traditional secure computation without mobile social networks. Here we regard the applications in mobile social networks as specific functions and stress on the achievement of fairness on these functions within mobile social networks in the presence of two rational parties. Rational parties value their utilities when they participate in secure computation protocol in mobile social networks. Therefore, we introduce reputation derived from mobile social networks into the utility definition such that rational parties have incentives to implement the applications for a higher utility. To the best of our knowledge, the protocol is the first fair secure computation in mobile social networks. Furthermore, it finishes within constant rounds and allows both parties to know the terminal round.

An Exact and Efficient Privacy-Preserving Spatiotemporal Matching in Mobile Social Networks

2016 ◽  
Vol 12 (2) ◽  
pp. 36-47 ◽  
Author(s):  
Xiuguang Li ◽  
Yuanyuan He ◽  
Ben Niu ◽  
Kai Yang ◽  
Hui Li
Keyword(s):  
Social Networks ◽  
Rapid Development ◽  
Security Analysis ◽  
Information Leakage ◽  
Privacy Preserving ◽  
Sensitive Information ◽  
Mobile Social Networks ◽  
Trust Relationships ◽  
Matching Schemes ◽  
Open Question

With the rapid development of mobile smartphone and its built-in location-aware devices, people are possible to establish trust relationships and further interaction with each other based their matched interests, hobbies, experiences, or spatiotemporal profiles. However, the possibility of sensitive information leakage and heavy computation overhead constrain the widespread use of the matching schemes in mobile social networks. Many privacy-preserving matching schemes were proposed recently years, but how to achieve privacy-preserving spatiotemporal matching exactly and efficiently remains an open question. In this paper, the authors propose a novel spatiotemporal matching scheme. The overlapping grid system is introduced into the scheme to improve the accuracy of spatiotemporal matching, and many repetitive records in a user's spatiotemporal profile are counted as one item so as to cut down the computation overhead. Their scheme decreases the spatiotemporal matching error, and promotes the efficiency of private matchmaking simultaneously. Thorough security analysis and evaluation results indicate that our scheme is effective and efficient.

scholarly journals Understanding Social Characteristic from Spatial Proximity in Mobile Social Network

2015 ◽  
Vol 10 (4) ◽  
pp. 539 ◽  
Author(s):  
Duan Hu ◽  
Benxiong Huang ◽  
Lai Tu ◽  
Shu Chen
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Mobile Devices ◽  
Hybrid Approach ◽  
Spatial Proximity ◽  
Mobile Social Networks ◽  
Mobile Social Network ◽  
Data Repositories ◽  
Sensing Applications ◽  
Proximity Matrix

Over the past decades, cities as gathering places of millions of people rapidly evolved in all aspects of population, society, and environments. As one recent trend, location-based social networking applications on mobile devices are becoming increasingly popular. Such mobile devices also become data repositories of massive human activities. Compared with sensing applications in traditional sensor network, Social sensing application in mobile social network, as in which all individuals are regarded as numerous sensors, would result in the fusion of mobile, social and sensor data. In particular, it has been observed that the fusion of these data can be a very powerful tool for series mining purposes. A clear knowledge about the interaction between individual mobility and social networks is essential for improving the existing individual activity model in this paper. We first propose a new measurement called geographic community for clustering spatial proximity in mobile social networks. A novel approach for detecting these geographic communities in mobile social networks has been proposed. Through developing a spatial proximity matrix, an improved symmetric nonnegative matrix factorization method (SNMF) is used to detect geographic communities in mobile social networks. By a real dataset containing thousands of mobile phone users in a provincial capital of China, the correlation between geographic community and common social properties of users have been tested. While exploring shared individual movement patterns, we propose a hybrid approach that utilizes spatial proximity and social proximity of individuals for mining network structure in mobile social networks. Several experimental results have been shown to verify the feasibility of this proposed hybrid approach based on the MIT dataset.

scholarly journals An Efficient Approach for LBS Privacy Preservation in Mobile Social Networks

2019 ◽  
Vol 9 (2) ◽  
pp. 316 ◽  
Author(s):  
Guangcan Yang ◽  
Shoushan Luo ◽  
Hongliang Zhu ◽  
Yang Xin ◽  
Mingzhen Li ◽  
...  
Keyword(s):  
Social Networks ◽  
Privacy Preservation ◽  
Rapid Development ◽  
Experimental Studies ◽  
Global Perspective ◽  
Handheld Devices ◽  
Mobile Social Networks ◽  
Daily Lives ◽  
Service Category ◽  
The Relationship

With the rapid development of smart handheld devices, wireless communication, and positioning technologies, location-based service (LBS) has been gaining tremendous popularity in mobile social networks (MSN). Users’ daily lives are facilitated by the applications of LBS, but users’ privacy leaking hinders the further development of LBS. In order to solve this problem, techniques such as k-anonymity and l-diversity have been widely adopted. However, most papers that combine with k-anonymity and l-diversity focus on the security of users’ privacy with little consideration of service efficiency. In this paper, we firstly treat the relationship between k-anonymity and l-diversity in the clustering process from a dynamic and global perspective. Then a service category table based algorithm (SCTB) is designed to identify and calculate l-diversity securely and efficiently, which promotes the cooperative efficiency of users in LBS query, especially when the preference privacy that users request in the clustering process have similarities. Finally, theoretical performance analysis and extensive experimental studies are performed to validate the effectiveness of our SCTB algorithm.

Cooperative Contents Distribution in Mobile Social Networks

2014 ◽  
Vol 36 (3) ◽  
pp. 613-625 ◽  
Author(s):  
Hai-Yang HU ◽  
Zhong-Jin LI ◽  
Hua HU ◽  
Ge-Hua ZHAO
Keyword(s):  
Social Networks ◽  
Mobile Social Networks

A Framework for Protecting Privacy on Mobile Social Networks

2021 ◽  
Author(s):  
Seyyed Mohammad Safi ◽  
Ali Movaghar ◽  
Komeil Safikhani Mahmoodzadeh
Keyword(s):  
Social Networks ◽  
Mobile Social Networks

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.

scholarly journals Preserving Secrecy in Mobile Social Networks

2020 ◽  
Vol 5 (1) ◽  
pp. 1-29 ◽  
Author(s):  
Gabriela Suntaxi ◽  
Aboubakr Achraf El Ghazi ◽  
Klemens Böhm
Keyword(s):  
Social Networks ◽  
Mobile Social Networks
Sign in / Sign up

Export Citation Format

Share Document