A Fog-based Approach to Secure Smart Grids Against Data Integrity Attacks

In this paper, a fog (edge) computing-based platform is proposed to realize distributed (localized) anomaly detection of data integrity attacks in smart grid applications aiming at addressing security and data privacy issues. To detect false data injection attacks, a distributed maximum likelihood (ML) estimator is implemented on the proposed fog-based platform. A series of simulation experiments are carried out to demonstrate the viability and efficacy of the proposed platform and, more importantly, of the distributed attack detection approach. The reported results, although preliminary in nature, move us a step closer to deploying fog computing technology in smart grid applications and in particular to further improving cyber-security of power networks.