A supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system

Abstract

Industrial Control Systems are part of our daily life in industries such as transportation, water, gas, oil, smart cities, and telecommunications. Technological development over time have improved their components including operating system platforms, hardware capabilities, and connectivity with networks inside and outside the organization. Consequently, the Industrial Control Systems components are exposed to sophisticated threats with weak security mechanism in place. This paper proposes a supervised energy monitoring-based machine learning approach for anomaly detection in a clean water supply system. A testbed of such a system is implemented using the Festo MPA Control Process Rig. The machine-learning algorithms, which include SVN, KNN, and Random Forest, perform classification tasks process in three different datasets obtained from the testbed. The algorithms are compared in terms of accuracy and F-measure. The results show that Random Forest achieves 5% better performance over KNN and SVM with small datasets and 4% regarding large datasets. For the time taken to build the model, KNN presents the best performance. However, its difference with Random Forest is smaller than with SVM.

PLC memory attack detection and response in a clean water supply system

“…In our previous work [22], we physically modelled a continuous clean water supply system using the default configuration of the Festo MPS PA Compact Workstation Rig. However, to make this experiment more realistic, we changed the configuration of the Festo Rig.…”

WaterLeakage: A Stealthy Malware for Data Exfiltration on Industrial Control Systems Using Visual Channels

“…However, we find out this threat model applicable in a scenario where the hacker is an insider who has access to the organisation [29]. We use a testbed implemented in our previous work [30] to demonstrate the effectiveness of this data exfiltration scenario.…”

“…In this paper, we use a model of a clean water supply system using the Festo MPS PA Compact Workstation Rig [31]. The operation of this control system is fully described in our previous work [30]. Fig 1 shows the testbed implemented for this paper.…”

Implementation and Detection of Novel Attacks to the PLC Memory of a Clean Water Supply System

“…In the author's previous work, the feasibility of detecting cyber attacks was demonstrated in a control process by monitoring the energy consumption of the pump [19]. In the first attempt, this was by monitoring the energy consumption of the ultrasonic sensor and the flowmeter; however, these sensors consume a low amount of energy which makes monitoring the energy consumption difficult.…”