Privacy preservation problems in online social networks

2012 ◽  
Author(s):  
Marius Kalinauskas
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Preservation

Privacy in Online Social Networks

2021 ◽  
pp. 2078-2109
Author(s):  
Ramanpreet Kaur ◽  
Tomaž Klobučar ◽  
Dušan Gabrijelčič
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Mitigation Strategies ◽  
Research Issues ◽  
Privacy Requirements ◽  
Privacy Threats

This chapter is concerned with the identification of the privacy threats to provide a feedback to the users so that they can make an informed decision based on their desired level of privacy. To achieve this goal, Solove's taxonomy of privacy violations is refined to incorporate the modern challenges to the privacy posed by the evolution of social networks. This work emphasizes on the fact that the privacy protection should be a joint effort of social network owners and users, and provides a classification of mitigation strategies according to the party responsible for taking these countermeasures. In addition, it highlights the key research issues to guide the research in the field of privacy preservation. This chapter can serve as a first step to comprehend the privacy requirements of online users and educate the users about their choices and actions in social media.

A privacy preservation method for multiple-source unstructured data in online social networks

2021 ◽  
pp. 102574
Author(s):  
Chenguang Wang ◽  
Zhu Tianqing ◽  
Ping Xiong ◽  
Wei Ren ◽  
Kim-Kwang Raymond Choo
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Preservation ◽  
Multiple Source ◽  
Unstructured Data ◽  
Preservation Method

Privacy Preservation in Decentralized Online Social Networks

2014 ◽  
Vol 18 (2) ◽  
pp. 16-23 ◽  
Author(s):  
Lorenz Schwittmann ◽  
Matthaus Wander ◽  
Christopher Boelmann ◽  
Torben Weis
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Preservation ◽  
Decentralized Online Social Networks

scholarly journals Trust evaluation based on evidence theory in online social networks

2018 ◽  
Vol 14 (10) ◽  
pp. 155014771879462 ◽  
Author(s):  
Jian Wang ◽  
Kuoyuan Qiao ◽  
Zhiyong Zhang
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Privacy Preservation ◽  
Evidence Theory ◽  
Trust Evaluation ◽  
Combination Rule ◽  
Privacy Leakage ◽  
Evidence Combination ◽  
Fixed Model ◽  
The Mean

Trust is an important criterion for access control in the field of online social networks privacy preservation. In the present methods, the subjectivity and individualization of the trust is ignored and a fixed model is built for all the users. In fact, different users probably take different trust features into their considerations when making trust decisions. Besides, in the present schemes, only users’ static features are mapped into trust values, without the risk of privacy leakage. In this article, the features that each user cares about when making trust decisions are mined by machine learning to be User-Will. The privacy leakage risk of the evaluated user is estimated through information flow predicting. Then the User-Will and the privacy leakage risk are all mapped into trust evidence to be combined by an improved evidence combination rule of the evidence theory. In the end, several typical methods and the proposed scheme are implemented to compare the performance on dataset Epinions. Our scheme is verified to be more advanced than the others by comparing the F-Score and the Mean Error of the trust evaluation results.

Privacy in Online Social Networks

2021 ◽  
pp. 567-598
Author(s):  
Ramanpreet Kaur ◽  
Tomaž Klobučar ◽  
Dušan Gabrijelčič
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Online Social Networks ◽  
Privacy Protection ◽  
Privacy Preservation ◽  
Mitigation Strategies ◽  
Research Issues ◽  
Privacy Requirements ◽  
Privacy Threats

This chapter is concerned with the identification of the privacy threats to provide a feedback to the users so that they can make an informed decision based on their desired level of privacy. To achieve this goal, Solove's taxonomy of privacy violations is refined to incorporate the modern challenges to the privacy posed by the evolution of social networks. This work emphasizes on the fact that the privacy protection should be a joint effort of social network owners and users, and provides a classification of mitigation strategies according to the party responsible for taking these countermeasures. In addition, it highlights the key research issues to guide the research in the field of privacy preservation. This chapter can serve as a first step to comprehend the privacy requirements of online users and educate the users about their choices and actions in social media.

scholarly journals An Empirical Study on the Privacy Preservation of Online Social Networks

IEEE Access ◽  
2018 ◽  
Vol 6 ◽  
pp. 19912-19922 ◽  
Author(s):  
Madhuri Siddula ◽  
Lijie Li ◽  
Yingshu Li
Keyword(s):  
Social Networks ◽  
Empirical Study ◽  
Online Social Networks ◽  
Privacy Preservation
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