@conference{iturberesa4ci2016,
author = "M. Iturbe and Camacho, Jos{\'e} and I. Garitano and U. Zurutuza and  R. Uribeetxeberria",
abstract = "Process Control Systems (PCSs) are the operating core of Critical Infrastructures (CIs). As such, anomaly detection  has  been  an  active  research  field  to  ensure  CI normal operation. Previous approaches have leveraged network level data for anomaly detection, or have disregarded the existence of process disturbances, thus opening the possibility of mislabelling disturbances as attacks and vice versa. In this paper we present an anomaly detection and diagnostic system based on Multivariate Statistical Process Control (MSPC), that aims to distinguish between attacks and disturbances. For this end, we expand traditional MSPC to monitor process level and controller level data. We evaluate our approach using the Tennessee-Eastman process. Results show that our approach can be used to distinguish disturbances from intrusions to a certain extent and we conclude that the proposed approach can be extended with other sources of data for improving results.",
booktitle = "3rd International Workshop on Reliability and Security Aspects for Critical Infrastructure Protection (resa4ci 2016)",
keywords = "Process control systems, Multivariate Statistical Process Control, Tennessee-Eastman",
title = "{O}n the {F}easibility of {D}istinguishing {B}etween {P}rocess {D}isturbances and {I}ntrusions in {P}rocess {C}ontrol {S}ystems using {M}ultivariate {S}tatistical {P}rocess {C}ontrol",
year = "2016",
}