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Intrusion Detection in Digital Twins for Industrial Control Systems

Akbarian, Fatemeh LU ; Fitzgerald, Emma LU orcid and Kihl, Maria LU (2020) 28 th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
Abstract
Nowadays, the growth of advanced technologies is paving the way for Industrial Control Systems (ICS) and making them more efficient and smarter. However, this makes ICS more connected to communication networks that provide a potential platform for attackers to intrude into the systems and cause damage and catastrophic consequences. In this paper, we propose implementing digital twins that have been equipped with an intrusion detection algorithm. Our novel algorithm is able to detect attacks in a timely manner and also diagnose the type of attack by classification of different types of attacks. With digital twins, which are a new concept in ICS, we have virtual replicas of physical systems so that they precisely mirror the internal behavior... (More)
Nowadays, the growth of advanced technologies is paving the way for Industrial Control Systems (ICS) and making them more efficient and smarter. However, this makes ICS more connected to communication networks that provide a potential platform for attackers to intrude into the systems and cause damage and catastrophic consequences. In this paper, we propose implementing digital twins that have been equipped with an intrusion detection algorithm. Our novel algorithm is able to detect attacks in a timely manner and also diagnose the type of attack by classification of different types of attacks. With digital twins, which are a new concept in ICS, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. So by placing the intrusion detection algorithm in digital twins, security tests can be done remotely without risking negative impacts on live systems. (Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
Intrusion detection, Digital twins, Industrial control systems
host publication
2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)
publisher
IEEE - Institute of Electrical and Electronics Engineers Inc.
conference name
28 th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2020)
conference location
Hvar, Croatia
conference dates
2020-09-17 - 2020-09-19
external identifiers
  • scopus:85096581749
ISBN
978-953-290-099-6
DOI
10.23919/SoftCOM50211.2020.9238162
project
Cyber Security for Next Generation Factory (SEC4FACTORY)
Nordic University Hub on Internet of Things
Ultra-reliable and low-latency networked systems aimed for time-critical services in an Industry 4.0 environment
language
English
LU publication?
yes
id
a0086e91-2cec-4d61-8ff4-d79883d84d2a
date added to LUP
2020-09-29 15:32:44
date last changed
2023-04-10 20:46:20
@inproceedings{a0086e91-2cec-4d61-8ff4-d79883d84d2a,
  abstract     = {{Nowadays, the growth of advanced technologies is paving the way for Industrial Control Systems (ICS) and making them more efficient and smarter. However, this makes ICS more connected to communication networks that provide a potential platform for attackers to intrude into the systems and cause damage and catastrophic consequences. In this paper, we propose implementing digital twins that have been equipped with an intrusion detection algorithm. Our novel algorithm is able to detect attacks in a timely manner and also diagnose the type of attack by classification of different types of attacks. With digital twins, which are a new concept in ICS, we have virtual replicas of physical systems so that they precisely mirror the internal behavior of the physical systems. So by placing the intrusion detection algorithm in digital twins, security tests can be done remotely without risking negative impacts on live systems.}},
  author       = {{Akbarian, Fatemeh and Fitzgerald, Emma and Kihl, Maria}},
  booktitle    = {{2020 International Conference on Software, Telecommunications and Computer Networks (SoftCOM)}},
  isbn         = {{978-953-290-099-6}},
  keywords     = {{Intrusion detection; Digital twins; Industrial control systems}},
  language     = {{eng}},
  publisher    = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
  title        = {{Intrusion Detection in Digital Twins for Industrial Control Systems}},
  url          = {{https://lup.lub.lu.se/search/files/84352829/Intrusion_Detection_in_Digital_Twins_for_Industrial_Control_Systems.pdf}},
  doi          = {{10.23919/SoftCOM50211.2020.9238162}},
  year         = {{2020}},
}