ICSML: Industrial Control Systems Machine Learning inference framework natively executing on IEC 61131-3 languages

by   Constantine Doumanidis, et al.

Industrial Control Systems (ICS) have played a catalytic role in enabling the 4th Industrial Revolution. ICS devices like Programmable Logic Controllers (PLCs), automate, monitor and control critical processes in industrial, energy and commercial environments. The convergence of traditional Operational Technology (OT) with Information Technology (IT) has opened a new and unique threat landscape. This has inspired defense research that focuses heavily on Machine Learning (ML) based anomaly detection methods that run on external IT hardware which means an increase in costs and the further expansion of the threat landscape. To remove this requirement, we introduce the ICS Machine Learning inference framework (ICSML) which enables the execution of ML models natively on the PLC. ICSML is implemented in IEC 61131-3 code and works around the limitations imposed by the domain-specific languages, providing a complete set of components for the creation of fully fledged ML models in a way similar to established ML frameworks. We then demonstrate a complete end-to-end methodology for creating ICS ML models using an external framework for training and ICSML for the PLC implementation. To evaluate our contributions we run a series of benchmarks studying memory and performance and compare our solution to the TFLite inference framework. Finally, to demonstrate the abilities of ICSML and to verify its non-intrusive nature, we develop and evaluate a case study of a real defense for process aware attacks against a Multi Stage Flash (MSF) desalination plant.


page 1

page 2

page 3

page 4


The Role of Machine Learning in Cybersecurity

Machine Learning (ML) represents a pivotal technology for current and fu...

SeLoC-ML: Semantic Low-Code Engineering for Machine Learning Applications in Industrial IoT

Internet of Things (IoT) is transforming the industry by bridging the ga...

Extraction of Complex DNN Models: Real Threat or Boogeyman?

Recently, machine learning (ML) has introduced advanced solutions to man...

Wild Networks: Exposure of 5G Network Infrastructures to Adversarial Examples

Fifth Generation (5G) networks must support billions of heterogeneous de...

The Machine Learning Bazaar: Harnessing the ML Ecosystem for Effective System Development

As machine learning is applied more and more widely, data scientists oft...

Machine Learning with DBOS

We recently proposed a new cluster operating system stack, DBOS, centere...

Please sign up or login with your details

Forgot password? Click here to reset