Social Networking Site Privacy Assurance and User Privacy Protection Behavior--Model

2020 ◽  
Author(s):  
Reza Mousavi ◽  
Rui Chen ◽  
Dan J. Kim ◽  
Kuanchin Chen
Author(s):  
Farzana Rahman ◽  
Md. Endadul Hoque ◽  
Ferdaus Ahmed Kawsar ◽  
Sheikh Iqbal Ahamed

2012 ◽  
Author(s):  
Lila M. Inglima ◽  
Jason C. Zeltser ◽  
Eric Schmidt ◽  
M. Blair Chinn ◽  
Katherine Price ◽  
...  

2014 ◽  
Vol 9 (2) ◽  
pp. 1-8
Author(s):  
Hana Esmaeel ◽  
Mustafa Laith Hussein ◽  
Afkar Abdul-Ellah ◽  
Abdul Jabbar

Libri ◽  
2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Zongda Wu ◽  
Chenglang Lu ◽  
Youlin Zhao ◽  
Jian Xie ◽  
Dongdong Zou ◽  
...  

Abstract This paper reviews a large number of research achievements relevant to user privacy protection in an untrusted network environment, and then analyzes and evaluates their application limitations in personalized information retrieval, to establish the conditional constraints that an effective approach for user preference privacy protection in personalized information retrieval should meet, thus providing a basic reference for the solution of this problem. First, based on the basic framework of a personalized information retrieval platform, we establish a complete set of constraints for user preference privacy protection in terms of security, usability, efficiency, and accuracy. Then, we comprehensively review the technical features for all kinds of popular methods for user privacy protection, and analyze their application limitations in personalized information retrieval, according to the constraints of preference privacy protection. The results show that personalized information retrieval has higher requirements for users’ privacy protection, i.e., it is required to comprehensively improve the security of users’ preference privacy on the untrusted server-side, under the precondition of not changing the platform, algorithm, efficiency, and accuracy of personalized information retrieval. However, all kinds of existing privacy methods still cannot meet the above requirements. This paper is an important study attempt to the problem of user preference privacy protection of personalized information retrieval, which can provide a basic reference and direction for the further study of the problem.


2020 ◽  
Vol 195 ◽  
pp. 105679
Author(s):  
Zongda Wu ◽  
Shigen Shen ◽  
Xinze Lian ◽  
Xinning Su ◽  
Enhong Chen

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