Intrusion Detection in Digital Twins for Industrial Control Systems
(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:
https://lup.lub.lu.se/record/a0086e91-2cec-4d61-8ff4-d79883d84d2a
- author
- Akbarian, Fatemeh LU ; Fitzgerald, Emma LU and Kihl, Maria LU
- organization
- publishing date
- 2020
- 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}}, }