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

Arifeen, Murshedul; Petrovski, Andrei; Petrovski, Sergei

Authors

Sergei Petrovski



Contributors

Naghmeh Moradpoor
Editor

Atilla El�i
Editor

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

Conference Name 14th International conference on Security of information and networks 2021 (SIN 2021)
Conference Location [virtual conference]
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 Mar 28, 2024
Publisher Institute of Electrical and Electronics Engineers (IEEE)
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

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