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.

Morality-Driven Data Forwarding With Privacy Preservation in Mobile Social Networks

2012 ◽  
Vol 61 (7) ◽  
pp. 3209-3222 ◽  
Author(s):  
Xiaohui Liang ◽  
Xu Li ◽  
Tom H. Luan ◽  
Rongxing Lu ◽  
Xiaodong Lin ◽  
...  
Keyword(s):  
Social Networks ◽  
Privacy Preservation ◽  
Mobile Social Networks ◽  
Data Forwarding

scholarly journals Community Core Evolution in Mobile Social Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
Hao Xu ◽  
Weidong Xiao ◽  
Daquan Tang ◽  
Jiuyang Tang ◽  
Zhenwen Wang
Keyword(s):  
Social Networks ◽  
Community Structure ◽  
Empirical Studies ◽  
Mobile Social Networks ◽  
The Real ◽  
Temporary Connection ◽  
Whole Process ◽  
Relationship Of ◽  
The Relationship ◽  
Stable Community

Community detection in social networks attracts a lot of attention in the recent years. Existing methods always depict the relationship of two nodes using the temporary connection. However, these temporary connections cannot be fully recognized as the real relationships when the history connections among nodes are considered. For example, a casual visit in Facebook cannot be seen as an establishment of friendship. Hence, our question is the following: how to cluster the real friends in mobile social networks? In this paper, we study the problem of detecting the stable community core in mobile social networks. The cumulative stable contact is proposed to depict the relationship among nodes. The whole process is divided into timestamps. Nodes and their connections can be added or removed at each timestamp, and historical contacts are considered when detecting the community core. Also, community cores can be tracked through the incremental computing, which can help to recognize the evolving of community structure. Empirical studies on real-world social networks demonstrate that our proposed method can effectively detect stable community cores in mobile social networks.

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.

scholarly journals Private Profile Matching for Mobile Social Networks Based on Fuzzy Extractors

10.29007/st23 ◽  
2018 ◽  
Author(s):  
Jaweher Zouari ◽  
Mohamed Hamdi ◽  
Tai-Hoon Kim
Keyword(s):  
Social Networks ◽  
Privacy Preservation ◽  
Homomorphic Encryption ◽  
Mobile Social Networks ◽  
Fuzzy Extractor ◽  
Mobile Social Networking ◽  
Profile Matching ◽  
Novel Approach ◽  
Privacy Breaches ◽  
Fuzzy Extractors

Interacting with geographically proximate users who present similar interests and preferences is a key service offered by mobile social networks which leads to the creation of new connections that combine physical and social closeness. Usually these interactions are based on social profile matching where users publish their preferences and attributes to enable the search for a similar profile. Such public search would result in the leakage of sensitive or identifiable information to strangers who are not always potential friends. As a consequence this promising feature of mobile social networking may cause serious privacy breaches if not addressed properly. Most existent work relies on homomorphic encryption for privacy preservation during profile matching, while we propose in this paper a novel approach based on the fuzzy extractor which performs private matching of two sets and reveals them only if they overlap considerably. Our scheme achieves a desirable trade off between security and complexity.

scholarly journals Privacy preservation in mobile social networks

2019 ◽  
Author(s):  
◽  
Douglas Steiert
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Privacy Preservation ◽  
Location Based Services ◽  
Mobile Social Networks ◽  
Privacy Concerns ◽  
Average Person ◽  
Effectiveness And Efficiency ◽  
Privacy Breaches

In this day and age with the prevalence of smartphones, networking has evolved in an intricate and complex way. With the help of a technology-driven society, the term "social networking" was created and came to mean using media platforms such as Myspace, Facebook, and Twitter to connect and interact with friends, family, or even complete strangers. Websites are created and put online each day, with many of them possessing hidden threats that the average person does not think about. A key feature that was created for vast amount of utility was the use of location-based services, where many websites inform their users that the website will be using the users' locations to enhance the functionality. However, still far too many websites do not inform their users that they may be tracked, or to what degree. In a similar juxtaposed scenario, the evolution of these social networks has allowed countless people to share photos with others online. While this seems harmless at face-value, there may be times in which people share photos of friends or other non-consenting individuals who do not want that picture viewable to anyone at the photo owner's control. There exists a lack of privacy controls for users to precisely de fine how they wish websites to use their location information, and for how others may share images of them online. This dissertation introduces two models that help mitigate these privacy concerns for social network users. MoveWithMe is an Android and iOS application which creates decoys that move locations along with the user in a consistent and semantically secure way. REMIND is the second model that performs rich probability calculations to determine which friends in a social network may pose a risk for privacy breaches when sharing images. Both models have undergone extensive testing to demonstrate their effectiveness and efficiency.

scholarly journals Task Allocation Model Based on Worker Friend Relationship for Mobile Crowdsourcing

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 921 ◽  
Author(s):  
Bingxu Zhao ◽  
Yingjie Wang ◽  
Yingshu Li ◽  
Yang Gao ◽  
Xiangrong Tong
Keyword(s):  
Social Networks ◽  
Task Allocation ◽  
Location Privacy ◽  
Rapid Development ◽  
Human Beings ◽  
Allocation Mechanism ◽  
Allocation Model ◽  
Mobile Crowdsourcing ◽  
System A ◽  
The Relationship

With the rapid development of mobile devices, mobile crowdsourcing has become an important research focus. According to the task allocation, scholars have proposed many methods. However, few works discuss combining social networks and mobile crowdsourcing. To maximize the utilities of mobile crowdsourcing system, this paper proposes a task allocation model considering the attributes of social networks for mobile crowdsourcing system. Starting from the homogeneity of human beings, the relationship between friends in social networks is applied to mobile crowdsourcing system. A task allocation algorithm based on the friend relationships is proposed. The GeoHash coding mechanism is adopted in the process of calculating the strength of worker relationship, which effectively protects the location privacy of workers. Utilizing synthetic dataset and the real-world Yelp dataset, the performance of the proposed task allocation model was evaluated. Through comparison experiments, the effectiveness and applicability of the proposed allocation mechanism were verified.

scholarly journals A Novel Method to Rank Influential Nodes in Complex Networks Based on Tsallis Entropy

Entropy ◽  
2020 ◽  
Vol 22 (8) ◽  
pp. 848 ◽  
Author(s):  
Xuegong Chen ◽  
Jie Zhou ◽  
Zhifang Liao ◽  
Shengzong Liu ◽  
Yan Zhang
Keyword(s):  
Social Networks ◽  
Rapid Development ◽  
Entropy Method ◽  
Tsallis Entropy ◽  
Network Nodes ◽  
Related Research ◽  
Novel Method ◽  
Influential Nodes ◽  
Rumor Control ◽  
The Relationship

With the rapid development of social networks, it has become extremely important to evaluate the propagation capabilities of the nodes in a network. Related research has wide applications, such as in network monitoring and rumor control. However, the current research on the propagation ability of network nodes is mostly based on the analysis of the degree of nodes. The method is simple, but the effectiveness needs to be improved. Based on this problem, this paper proposes a method that is based on Tsallis entropy to detect the propagation ability of network nodes. This method comprehensively considers the relationship between a node’s Tsallis entropy and its neighbors, employs the Tsallis entropy method to construct the TsallisRank algorithm, and uses the SIR (Susceptible, Infectious, Recovered) model for verifying the correctness of the algorithm. The experimental results show that, in a real network, this method can effectively and accurately evaluate the propagation ability of network nodes.

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.

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