CyberSenseIT

The objective of the CyberSenseIT project is to investigate and design an innovative framework enabling reliable IoT scenarios (such as crowdsensing, smart buildings, or smart homes) and the automated detection of cyberattacks, especially entailing sensors misbehaviors that may affect the trust level of individual nodes taking part in the scenario. Artificial Intelligence (AI) techniques will be used by the CyberSenseIT framework to detect attacks, since it has been outlined in the literature that ML/DL (Machine Learning/Deep Learning) approaches are most promising to mitigate limitations of traditional solutions regarding unseen and new families of cyberattacks.

The framework overall performance will be carefully considered by initially analyzing dimensions and features able to model the normal behavior of the IoT device as well as the behavior of several cyberattacks affecting resource-constrained devices belonging to crowdsensing platforms. Finally, different Key Performance Indicators (KPI) will be defined to measure and report after the project ends on performance under different potential misconfigurations and cyberattack scenarios.

• University of Zurich, IFI, CSG
• Armasuisse
• University of Murcia 

• Prof. Dr. Burkhard Stiller
• Dr. Alberto Huertas Celdrán

Inquiries may be directed to the local Swiss project management: