| Title | Detection of Integrity Attacks to Smart Grids Using Process Mining and Time-Evolving Graphs |
| Publication Type | Conference Paper |
| Year of Publication | 2018 |
| Authors | Bernardi, S., Trillo-Lado, R., Merseguer, J. |
| Conference Name | 2018 14th European Dependable Computing Conference (EDCC) |
| Keywords | anomaly detection, Attack Graphs, composability, data mining, Frequency measurement, graph theory, integrity attack, integrity attacks, Ireland Commission for Energy Regulation, Meters, Metrics, power engineering computing, power system security, process mining, pubcrawl, resilience, Resiliency, Smart grids, smart meters, smart power grids, time evolving graphs, time-evolving graphs, work-in-progress approach |
| Abstract | 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). |
| DOI | 10.1109/EDCC.2018.00032 |
| Citation Key | bernardi_detection_2018 |
Detection of Integrity Attacks to Smart Grids Using Process Mining and Time-Evolving Graphs