Title :
Deploying and Evaluating Pufferfish Privacy for Smart Meter Data
Author :
Stephan Kessler;Erik Buchmann; B?hm
Author_Institution :
Karlsruhe Inst. for Technol., Karlsruhe, Germany
Abstract :
Realizing a Smart Grid without sacrificing the privacy of consumers is a challenging problem. Data-centric approaches like Puffer fish ensure privacy by transforming data so that certain user-specified information, so-called secrets, cannot be inferred. Deploying Puffer fish on smart-meter data requires application-specific decisions, i.e., A general definition of secrets in time series. We investigate how to perturb energy consumption data in this manner, and we quantify the trade off between privacy and utility.
Keywords :
"Data privacy","Time series analysis","Privacy","Heating","Smart grids","Smart meters","Correlation"
Conference_Titel :
Ubiquitous Intelligence and Computing and 2015 IEEE 12th Intl Conf on Autonomic and Trusted Computing and 2015 IEEE 15th Intl Conf on Scalable Computing and Communications and Its Associated Workshops (UIC-ATC-ScalCom), 2015 IEEE 12th Intl Conf on
DOI :
10.1109/UIC-ATC-ScalCom-CBDCom-IoP.2015.55