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InSecTT Technologies for the Enhancement of Industrial Security and Safety
Mälardalen University, Sweden.
Mälardalen University, Sweden.
Mälardalen University, Sweden.
ABB AB, Sweden.
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2024 (English)In: Intelligent secure trustable things, Springer Science and Business Media Deutschland GmbH , 2024, Vol. 1147, p. 83-104Chapter in book (Other academic)
Abstract [en]

The recent advances in digitalization, improved connectivity and cloud based services are making a huge revolution in manufacturing domain. In spite of the huge potential benefits in productivity, these trends also bring in some concerns related to safety and security to the traditionally closed industrial operation scenarios. This paper presents a high-level view of some of the research results and technological contributions of the InSecTT Project for meeting safety/security goals. These technology contributions are expected to support both the design and operational phases in the production life cycle. Specifically, our contributions spans enforcing stricter but flexible access control, evaluation of machine learning techniques for intrusion detection, generation of realistic process control and network oriented datasets with injected anomalies and performing safety and security analysis on automated guided vehicle platoons.

Place, publisher, year, edition, pages
Springer Science and Business Media Deutschland GmbH , 2024. Vol. 1147, p. 83-104
Series
Studies in Computational Intelligence (SCI,volume 1147)
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:ri:diva-74784DOI: 10.1007/978-3-031-54049-3_5Scopus ID: 2-s2.0-85200487605OAI: oai:DiVA.org:ri-74784DiVA, id: diva2:1892649
Available from: 2024-08-27 Created: 2024-08-27 Last updated: 2025-09-23Bibliographically approved

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Dehlaghi Ghadim, Alireza

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