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Published in: Social Network Analysis and Mining 1/2018

01-12-2018 | Review Article

An investigation into the requirements of privacy in social networks and factors contributing to users’ concerns about violation of their privacy

Authors: Razieh Malekhosseini, Mehdi Hosseinzadeh, Keyvan Navi

Published in: Social Network Analysis and Mining | Issue 1/2018

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Abstract

Social networks are specific types of social media which consolidate the ability of omnipresent connection for users and devices to share user-centric data objects among interested users. Taking advantage of the characteristics of both mobile social networks (MSNs) and online social networks (OSNs), MSNs are capable of providing an efficient and effective mobile environment for users to access, distribute, and share data. OSNs provide capability of search, data sharing, and online social interactions for users through Internet sites. However, the lack of a protective infrastructure in these networks has turned them into convenient targets for various risks. This is the main purpose why social networks including MSNs and OSNs carry disparate and intricate safety concerns specially privacy-preserving challenges and what has been done to improve these challenges. In addition, what types of data should be protected and what are the different architectures provided for each of these networks? In this paper, we aim to provide a clear categorization on privacy challenges and a deep exploration over some recent solutions in MSNs and OSNs. In particular, in MSNs, proposed scheme to protect data types is categorized, and in OSNs, all types of proposed architectures, along with the proposed mechanisms for privacy, are classified. To conclude, several major open research issues are discussed, and future research directions are outlined.

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Metadata
Title
An investigation into the requirements of privacy in social networks and factors contributing to users’ concerns about violation of their privacy
Authors
Razieh Malekhosseini
Mehdi Hosseinzadeh
Keyvan Navi
Publication date
01-12-2018
Publisher
Springer Vienna
Published in
Social Network Analysis and Mining / Issue 1/2018
Print ISSN: 1869-5450
Electronic ISSN: 1869-5469
DOI
https://doi.org/10.1007/s13278-018-0518-x

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