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http://dx.doi.org/10.13089/JKIISC.2015.25.5.1001

Threatening privacy by identifying appliances and the pattern of the usage from electric signal data  

Cho, Jae yeon (School of Information Security, Korea University)
Yoon, Ji Won (School of Information Security, Korea University)
Publication Information
Journal of the Korea Institute of Information Security & Cryptology / v.25, no.5, 2015 , pp. 1001-1009 More about this Journal
Abstract
In Smart Grid, smart meter sends our electric signal data to the main server of power supply in real-time. However, the more efficient the management of power loads become, the more likely the user's pattern of usage leaks. This paper points out the threat of privacy and the need of security measures in smart device environment by showing that it's possible to identify the appliances and the specific usage patterns of users from the smart meter's data. Learning algorithm PCA is used to reduce the dimension of the feature space and k-NN Classifier to infer appliances and states of them. Accuracy is validated with 10-fold Cross Validation.
Keywords
Smart meter; Privacy; PCA; k-NN Classifier; 10-fold Cross Validation;
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