Biblio

Filters: Author is Bao, J.  [Clear All Filters]
2018-09-28
Cao, H., Liu, S., Zhao, R., Gu, H., Bao, J., Zhu, L..  2017.  A Privacy Preserving Model for Energy Internet Base on Differential Privacy. 2017 IEEE International Conference on Energy Internet (ICEI). :204–209.

Comparing with the traditional grid, energy internet will collect data widely and connect more broader. The analysis of electrical data use of Non-intrusive Load Monitoring (NILM) can infer user behavior privacy. Consideration both data security and availability is a problem must be addressed. Due to its rigid and provable privacy guarantee, Differential Privacy has proverbially reached and applied to privacy preserving data release and data mining. Because of its high sensitivity, increases the noise directly will led to data unavailable. In this paper, we propose a differentially private mechanism to protect energy internet privacy. Our focus is the aggregated data be released by data owner after added noise in disaggregated data. The theoretically proves and experiments show that our scheme can achieve the purpose of privacy-preserving and data availability.