Visible to the public Developing Battery of Vulnerability Tests for Industrial Control Systems

TitleDeveloping Battery of Vulnerability Tests for Industrial Control Systems
Publication TypeConference Paper
Year of Publication2019
AuthorsFujdiak, Radek, Blazek, Petr, Mlynek, Petr, Misurec, Jiri
Conference Name2019 10th IFIP International Conference on New Technologies, Mobility and Security (NTMS)
Keywordsattack vector, computer network security, connected environment, control engineering computing, data generator, ICS area, ICS networks, ICS/IDS systems, IEC standards, Industrial Communication, industrial control, industrial control systems, Industrial Control Systems Anomaly Detection, Information security, Integrated circuit modeling, Intrusion detection, Intrusion Detection Systems, intrusion prevention systems, production engineering computing, Protocols, pubcrawl, resilience, Resiliency, Scalability, security, Servers, test environment, vulnerability tests
Abstract

Nowadays, the industrial control systems (ICS) face many challenges, where security is becoming one of the most crucial. This fact is caused by new connected environment, which brings among new possibilities also new vulnerabilities, threats, or possible attacks. The criminal acts in the ICS area increased over the past years exponentially, which caused the loss of billions of dollars. This also caused classical Intrusion Detection Systems and Intrusion Prevention Systems to evolve in order to protect among IT also ICS networks. However, these systems need sufficient data such as traffic logs, protocol information, attack patterns, anomaly behavior marks and many others. To provide such data, the requirements for the test environment are summarized in this paper. Moreover, we also introduce more than twenty common vulnerabilities across the ICS together with information about possible risk, attack vector (point), possible detection methods and communication layer occurrence. Therefore, the paper might be used as a base-ground for building sufficient data generator for machine learning and artificial intelligence algorithms often used in ICS/IDS systems.

DOI10.1109/NTMS.2019.8763810
Citation Keyfujdiak_developing_2019