Developing Predictable and Secure IoT for Autonomous Systems

The goal of iSecure is to design and develop secure digital platforms leveraging the edge, fog and cloud computing for enhancing development, production and support. 

On the one hand, current digital platform architectures for IoT lack of timing guarantees for short-latency data communication among the IoT devices. On the other hand, they lack proper mechanism for data privacy and security. iSecure proposed solution consists of designing and developing an architecture towards secure digital platforms ensuring guarantees on short-latency, privacy and security of data. Edge nodes will serve as local controllers for multiple IoT devices, allowing direct communication between devices controlled by the same node and communication between devices on different nodes, via the nodes. This provides for short-latency communication and data security. The global cloud will orchestrate all edge nodes. Each IoT domain consists of multiple IoT devices that communicate with the edge node using time predictable TSCH technology. We propose a dynamic scheduling algorithm for TSCH to accommodate a changing environment, with mobile devices or new additions/removals. SDN will be utilized to dynamically manage communication bandwidth within each IoT domain. To ensure security and confidentiality, the architecture will employ best practices, innovative techniques, and hardware support for confidential computing. iSecure will achieve the following outcomes: 

• A secure edge-cloud architecture with dynamic and time-predictable communication for IoT systems in industrial environments. 
• A confidential data sharing platform for devices, systems and services. 
• Proof-of-concept implementations in two use cases namely autonomous airport and harbour. 
• Commercialization of the secure, data sharing platform in relevant industrial contexts in Sweden and abroad.

[Show all publications]

Engineering Future Critical CPSs with Trustworthy GenAI Across the Lifecycle (Apr 2026)
Alessio Bucaioni, Antonio Cicchetti, Gordana Dodig-Crnkovic, Romina Spalazzese , Emma Söderberg , Dániel Varró
48th IEEE/ACM International Conference on Software Engineering (ICSE 2026)

Technical Credit: Industry Views on Benefits and Barriers (Apr 2026)
Alessio Bucaioni, Ian Gorton , Patrizio Pelliccione
48th IEEE/ACM International Conference on Software Engineering (ICSE 2026)

Reducing IoT Data at the Edge: A Comparative Evaluation (Mar 2026)
Sebastian Leclerc, Emma Hansen , Alessio Bucaioni, Mohammad Ashjaei
IEEE International Conference on Industrial Technology (ICIT 2026) (ICIT26)

From Engineering Models to Digital Twins: Generating AAS from SysML v2 Models (Nov 2025)
Enxhi Ferko, Luca Berardinelli , Alessio Bucaioni, Moris Behnam, Manuel Wimmer
Journal of Systems and Software (JSS)

A Checklist of Quality Concerns for Architecting ML-Intensive Systems (Oct 2025)
Alessio Bucaioni, Rick Kazman , Patrizio Pelliccione
Journal of Systems and Software (JSS)

Learning to Transform: Evaluating LLMs on Model Transformation by Example (Oct 2025)
Duy Dao, Alessio Bucaioni, Antonio Cicchetti
MDE Intelligence 2025 (MDE Int 25)