Robust Demand Response for Device Scheduling under False Data Injection Attacks in Smart Grids

Utilities are required to exchange data with home energy management systems (HEMS) for the realization of efficient demand response (DR) systems. Dependability of DR schemes on HEMSs opens new attack vectors for adversaries, as HEMSs are outside the control of utilities. Adversaries, as well as authentic users, can execute false data injection attacks (FDIA) to manipulate these systems without causing significant security breaches, unlike in traditional FDIAs. Despite the research on FDIAs and attack detection on smart grids, comparatively less amount of work looked into the robustness of distributed DR schemes against FDIAs. To address that gap, we propose a robust abstracted device scheduling architecture. The proposed architecture utilizes both attack detection and impacts mitigation strategies, as it can be leveraged to improve the robustness of distributed DR schemes in the future smart grids.