Detection of Integrity Attacks to Smart Grids using Process Mining and Time-Evolving Graphs

In this paper, we present a work-in-progress approach to detect integrity attacks to Smart Grids by analyzing the readings from smart meters. Our approach is based on process mining and time-evolving graphs. In particular, process mining is used to discover graphs, from the dataset collecting the readings over a time period, that represent the behaviour of a customer. The time-evolving graphs are then compared in order to detect anomalous behavior of a customer. To evaluate the feasibility of our approach, we have conducted preliminary experiments by using the dataset provided by the Ireland's Commission for Energy Regulation (CER).