LAUSR

The availability of individual load curves per household in the smart grid end-user domain combined with nonintrusive load monitoring (NILM) to infer personal data from these load curves has led to privacy concerns. Based on insights of the interrelation of load profile resolution and accuracy of NILM techniques, we propose the use of the wavelet transform to represent load data in multiple resolutions. Each resolution is encrypted with a different key using an appropriate cipher and a hierarchical keying scheme. End-to-end security ensures access control. To meet requirements of low computational complexity in low-cost smart meters, the lifting implementation of the wavelet transform is used to generate multiple resolutions. It is shown that the multiresolution approach is compatible with other privacy-enhancing technologies, such as secure signal processing. This allows adding new degrees of freedom to these methods by introducing the dimension of multiple resolutions. The proposed approach is evaluated based on the provided level of privacy and security, computational demands, and feasibility in an economic sense.