Utility analysis on privacy-preservation algorithms for online social networks: an empirical study

2019 ◽  
Author(s):  
Cheng Zhang ◽  
Honglu Jiang ◽  
Xiuzhen Cheng ◽  
Feng Zhao ◽  
Zhipeng Cai ◽  
...  
Keyword(s):  
Social Networks ◽  
Empirical Study ◽  
Online Social Networks ◽  
Privacy Preservation ◽  
Utility Analysis

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

scholarly journals Defining Inspection Techniques for Detecting Privacy Problems in Online Social Networks

2019 ◽  
Vol 10 ◽  
pp. 35
Author(s):  
Andrey  Rodrigues ◽  
Natasha  M. C. Valentim ◽  
Eduardo  Feitosa
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Empirical Study ◽  
Qualitative Analysis ◽  
Online Social Networks ◽  
Online Social Network ◽  
Effective Alternative ◽  
Daily Lives ◽  
Study Participants ◽  
Inspection Techniques

In the last few years, Online Social Networks (OSN) have experienced growth in the number of users, becoming an increasingly embedded part of people’s daily lives. Privacy expectations of OSNs are higher as more members start realizing potential privacy problems they face by interacting with these systems. Inspection methods can be an effective alternative for addressing privacy problems because they detect possible defects that could be causing the system to behave in an undesirable way. Therefore, we proposed a set of privacy inspection techniques called PIT-OSN (Privacy Inspection Techniques for Online Social Network). This paper presents the description and evolution of PIT-OSN through the results of a preliminary empirical study. We discuss the quantitative and qualitative results and their impact on improving the techniques. Results indicate that our techniques assist non-expert inspectors uncover privacy problems effectively, and are considered easy to use and useful by the study participants. Finally, the qualitative analysis helped us improve some technique steps that might be unclear.

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
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