Hans Hansson

Alireza Dehlaghi-Ghadim, Mahshid Helali Moghadam, Ali Balador et al.

Over the past few decades, Industrial Control Systems (ICSs) have been targeted by cyberattacks and are becoming increasingly vulnerable as more ICSs are connected to the internet. Using Machine Learning (ML) for Intrusion Detection Systems (IDS) is a promising approach for ICS cyber protection, but the lack of suitable datasets for evaluating ML algorithms is a challenge. Although there are a few commonly used datasets, they may not reflect realistic ICS network data, lack necessary features for effective anomaly detection, or be outdated. This paper presents the 'ICS-Flow' dataset, which offers network data and process state variables logs for supervised and unsupervised ML-based IDS assessment. The network data includes normal and anomalous network packets and flows captured from simulated ICS components and emulated networks. The anomalies were injected into the system through various attack techniques commonly used by hackers to modify network traffic and compromise ICSs. We also proposed open-source tools, `ICSFlowGenerator' for generating network flow parameters from Raw network packets. The final dataset comprises over 25,000,000 raw network packets, network flow records, and process variable logs. The paper describes the methodology used to collect and label the dataset and provides a detailed data analysis. Finally, we implement several ML models, including the decision tree, random forest, and artificial neural network to detect anomalies and attacks, demonstrating that our dataset can be used effectively for training intrusion detection ML models.

Kaj Hänninen, Hans Hansson, Henrik Thane et al.

In the early 90s, researchers began to focus on security as an important property to address in combination with safety. Over the years, researchers have proposed approaches to harmonize activities within the safety and security disciplines. Despite the academic efforts to identify interdependencies and to propose combined approaches for safety and security, there is still a lack of integration between safety and security practices in the industrial context, as they have separate standards and independent processes often addressed and assessed by different organizational teams and authorities. Specifically, security concerns are generally not covered in any detail in safety standards potentially resulting in successfully safety-certified systems that still are open for security threats from e.g., malicious intents from internal and external personnel and hackers that may jeopardize safety. In recent years security has again received an increasing attention of being an important issue also in safety assurance, as the open interconnected nature of emerging systems makes them susceptible to security threats at a much higher degree than existing more confined products.This article presents initial ideas on how to extend safety work to include aspects of security during the context establishment and initial risk assessment procedures. The ambition of our proposal is to improve safety and increase efficiency and effectiveness of the safety work within the frames of the current safety standards, i.e., raised security awareness in compliance with the current safety standards. We believe that our proposal is useful to raise the security awareness in industrial contexts, although it is not a complete harmonization of safety and security disciplines, as it merely provides applicable guidance to increase security awareness in a safety context.