Abstract
With the advent of smart grids, there can be two-way communications between the users and the electricity company through the power grids. This allows two promising features, namely energy auditing and energy scheduling. These features enable better energy efficiency as well as pervasive energy analysis. However, the grid can become vulnerable if an adequate system, which eliminates potential threats arising from the massive data exchange, is not present. In this dissertation, we propose a back-to-front framework which jointly secures user privacy as well as improves the energy consumption distribution. This dissertation is divided into two parts. In the first part, we will show a compressive sensing (CS) based approach which enhances data fidelity and security in energy auditing network. Then, in the second part, a truthful mechanism for energy scheduling will be given.