Developing Predictable and Secure IoT for Autonomous Systems

Status:

active

End date:

2026-10-31

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]

Continuous Conformance of Software Architectures (Jun 2024)
Alessio Bucaioni, Amleto Di Salle , Ludovico Iovino , Leonardo Mariani , Patrizio Pelliccione
21st IEEE International Conference on Software Architecture (ICSA 2024)

Evolution of an Automotive Modelling Language for Enhanced Support of Diverse Network Interface Controllers (Feb 2024)
Alessio Bucaioni, Saad Mubeen
International Conference on Artificial Intelligence, Control, Data Sciences and Applications 2024 (ACDSA 2024)

Programming with ChatGPT: How far can we go? (Feb 2024)
Vilma Helander , Hampus Ekedahl , Alessio Bucaioni, Thanh Phuong Nguyen
Machine Learning with Applications (MLWA)

Model Based Trustworthiness Evaluation of Autonomous Cyber-Physical Production Systems: A Systematic Mapping Study (Jan 2024)
Maryam Zahid, Alessio Bucaioni, Francesco Flammini
ACM Computing Surveys (CSUR)

Analysis of log files to enable smart-troubleshooting in Industry 4.0: a systematic mapping study (Dec 2023)
Sania Partovian, Alessio Bucaioni, Francesco Flammini, Johan Thornadtsson
Journal of IEEE Access (IEEE-Access)

PartnerType
Addiva Industrial
Canarybit Industrial
Senseair Industrial
Västerås Flygplats Municipalities and others
Västerås Mälarhamnar Municipalities and others

Alessio Bucaioni, Assistant Professor

Email: alessio.bucaioni@mdh.se
Room: U1-067
Phone: +46736620711