Private Data Analysis via Output Perturbation

Author(s):  
Kobbi Nissim
Keyword(s):  
CHANCE ◽  
2020 ◽  
Vol 33 (4) ◽  
pp. 37-42
Author(s):  
Marco Avella-Medina

2014 ◽  
Vol 7 (8) ◽  
pp. 637-648 ◽  
Author(s):  
Davide Proserpio ◽  
Sharon Goldberg ◽  
Frank McSherry
Keyword(s):  

2010 ◽  
Vol 45 (1) ◽  
pp. 151-159 ◽  
Author(s):  
Michal Sramka

ABSTRACTMany databases contain data about individuals that are valuable for research, marketing, and decision making. Sharing or publishing data about individuals is however prone to privacy attacks, breaches, and disclosures. The concern here is about individuals’ privacy-keeping the sensitive information about individuals private to them. Data mining in this setting has been shown to be a powerful tool to breach privacy and make disclosures. In contrast, data mining can be also used in practice to aid data owners in their decision on how to share and publish their databases. We present and discuss the role and uses of data mining in these scenarios and also briefly discuss other approaches to private data analysis.


2017 ◽  
Vol 13 (4) ◽  
pp. 1-38
Author(s):  
Elaine Shi ◽  
T.-H. Hubert Chan ◽  
Eleanor Rieffel ◽  
Dawn Song
Keyword(s):  

Author(s):  
Tianqing Zhu ◽  
Gang Li ◽  
Wanlei Zhou ◽  
Philip S. Yu
Keyword(s):  

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