Artificial Intelligence of Things (AIoT) is the natural evolution for both Artificial Intelligence (AI) and Internet of Things (IoT) because they are mutually beneficial. AI increases the value of the IoT through machine learning by transforming the data into useful information, while the IoT increases the value of AI through connectivity and data exchange. Therefore, InSecTT – Intelligent Secure Trustable Things, a pan-European effort with 54 key partners from 12 countries (EU and Turkey), will provide intelligent, secure and trustworthy systems for industrial applications to provide comprehensive cost-efficient solutions of intelligent, end-to-end secure, trustworthy connectivity and interoperability to bring the Internet of Things and Artificial Intelligence together. InSecTT aims at creating trust in AI-based intelligent systems and solutions as a major part of the AIoT, i.e. moving AI to the edge and making AI and ML based systems trustable, explainable and not just a black box. InSecTT will foster cooperation between big industrial players from various domains, a number of highly innovative SMEs distributed all over Europa and cutting-edge research organisations and university. The project features a big variety of industry-driven use cases embedded into various application domains, i.e. smart infrastructure, building, manufacturing, automotive, aeronautics, railway, urban public transport, maritime as well as health. The demonstration of InSecTT solutions in well-known real-world environments like trains, ports, airports and the health sector will generate huge impact on both high and broad level, going from citizens up to European stakeholders. It will establish the EU as a center of intelligent, secure and trustworthy systems for industrial applications enabled by a strong industry with a strong reputation and an informed society, in order to enable products and services based on AI compliant to European values and “Made in Europe".
Project Website: https://insectt.eu
MDH Media posts
Learning single and compound-protocol automata and checking behavioral equivalences (Apr 2025) Stefan Marksteiner, David Schögler , Marjan Sirjani, Mikael Sjödin International Journal on Software Tools for Technology Transfer (STTT)
Evaluation of an OPC UA-based Access Control Enforcement Architecture (Sep 2024) Björn Leander, Aida Causevic, Tomas Lindström , Hans Hansson 28th European Symposium on Research in Computer Security (ESORICS 2023)
Network intrusion detection using machine learning on resource-constrained edge devices (Jul 2024) Pontus Lidholm , Tijana Markovic, Miguel Leon Ortiz, Per Erik Strandberg International Conference on Neural Networks (IJCNN 24)
Random forest with differential privacy in federated learning framework for network attack detection and classification (Jun 2024) Tijana Markovic, Miguel Leon Ortiz, David Buffoni , Sasikumar Punnekkat Applied Intelligence (APIN)
InSecTT Technologies for the Enhancement of Industrial Security and Safety (Jun 2024) Sasikumar Punnekkat, Tijana Markovic, Miguel Leon Ortiz, Björn Leander, Alireza Dehlaghi Ghadim, Per Erik Strandberg Intelligent Secure Trustable Things, Studies in Computational Intelligence (SCI), Springer (SCI-INSECTT)
Approaches For Automating Cybersecurity Testing Of Connected Vehicles (Jun 2024) Stefan Marksteiner, Peter Priller , Markus Wolf