Automated microsegmentation for lateral movement prevention in industrial Internet of Things (IIoT).

Arifeen, Murshedul; Petrovski, Andrei; Petrovski, Sergei

Abstract

The integration of the IoT network with the Operational Technology (OT) network is increasing rapidly. However, this incorporation of IoT devices into the OT network makes the industrial control system vulnerable to various cyber threats. Hacking an IoT device at the network edge, an attacker can move laterally to compromise the main control server and manipulate the whole control system of the industrial infrastructure. In this paper, we have proposed an automated Micro-segmentation (MS) model based on Machine Learning (ML) algorithms to reduce the lateral movement of an attacker or malware. The proposed model generates the micro-segments based on network traffic and blocks the malicious traffic at each segment. We have taken UNSW-NB15 and IoTID20 datasets for our experiments. Experimental results show that after generating micro-segments and separating the normal traffic, the model limits redundant links and blocks malicious traffic. Limiting the usage of redundant links reduces the lateral movement or spreading of malware. We also considered the deterministic epidemic model to analyze the device infection rate due to lateral movement or malware propagation.

Citation

ARIFEEN, M., PETROVSKI, A. and PETROVSKI, S. 2021. Automated microsegmentation for lateral movement prevention in industrial Internet of Things (IIot). In Moradpoor, N., Elçi, A. and Petrovski, A. (eds.) Proceedings of 14th International conference on Security of information and networks 2021 (SIN 2021), 15-17 December 2021, [virtual conference]. Piscataway: IEEE [online], article 28. Available from: https://doi.org/10.1109/SIN54109.2021.9699232

• Presentation Conference Type: Conference Paper (published)
• Conference Name: 14th International conference on Security of information and networks 2021 (SIN 2021)
• Start Date: Dec 15, 2021
• End Date: Dec 17, 2021
• Acceptance Date: Dec 7, 2021
• Online Publication Date: Feb 10, 2022
• Publication Date: Dec 17, 2021
• Deposit Date: Feb 11, 2022
• Publicly Available Date: Feb 11, 2022
• Publisher: Institute of Electrical and Electronics Engineers (IEEE)
• Peer Reviewed: Peer Reviewed
• Book Title: Proceedings of the 14th International conference on Security of information and networks 2021 (SIN 2021)
• ISBN: 9781728192666
• DOI: https://doi.org/10.1109/SIN54109.2021.9699232
• Keywords: Internet of Things; Micro-segmentation; Security; Lateral movement; Machine learning
• Public URL: https://rgu-repository.worktribe.com/output/1592299