scholarly journals A New Framework for Privacy-Preserving Aggregation of Time-Series Data

2016 ◽  
Vol 18 (3) ◽  
pp. 1-21 ◽  
Author(s):  
Fabrice Benhamouda ◽  
Marc Joye ◽  
BenoîT Libert
Author(s):  
Chang Xu ◽  
Run Yin ◽  
Liehuang Zhu ◽  
Chuan Zhang ◽  
Can Zhang ◽  
...  

2019 ◽  
Vol 8 (4) ◽  
pp. 4418-4421

It is instead required for IoT units to equip along with the potential to withstand security and privacy threats when fulfilling the intended useful criteria and services. To obtain these targets, there are many brand-new problems for the IoT to apply personal privacy-preserving records manipulation. Initially, data professionals need to have to process privacysensitive data to remove the counted on details without particular privacy enclosure. Within this paper, our company temporarily showed the kinds of security concerns in IoT style, personal privacy-preserving in different IoT devices as well as additional challenges and also method for privacy-preserving time-series data publishing


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