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InSecTT Technologies for the Enhancement of Industrial Security and Safety


Publication Type:

Book chapter


Intelligent Secure Trustable Things, Studies in Computational Intelligence (SCI), Springer





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 (a) enforcing stricter but flexible access control, (b) evaluation of machine learning techniques for intrusion detection, (c) generation of realistic process control and network oriented datasets with injected anomalies and (d) performing safety and security analysis on automated guided vehicle platoons.


author = {Sasikumar Punnekkat and Tijana Markovic and Miguel Leon Ortiz and Bj{\"o}rn Leander and Alireza Dehlaghi Ghadim and Per Erik Strandberg},
title = {InSecTT Technologies for the Enhancement of Industrial Security and Safety},
isbn = {978-3-031-54048-6},
editor = {Michael Karner, Johannes Peltola, Michael Jerne, Lukas Kulas, Peter Priller},
volume = {1147},
month = {June},
year = {2024},
booktitle = {Intelligent Secure Trustable Things, Studies in Computational Intelligence (SCI), Springer},
publisher = { Springer},
url = {}