Internet of Things (IoT) security through machine learning and data sharing (SunRISE-ECTM)

Themes: Micro/Nano System Integration and Reliability

Today about 50 billion connected devices are on the market, connected devices do deliver clear benefits, but they also increase the risk of data manipulation, data theft and cyberattack. To obtain a comprehensive security solution, SunRISE addresses several key aspects, critical in future IoT systems.

To achieve the SunRISE objectives, the consortium will focus on the following key innovations:

  • Machine learning on the edge nodes, for IoT security analytics and anomaly detection
  • Cloud platform applying machine learning techniques for sharing relevant security data
  • Homomorphic encryption as privacy-enhancing technology for Industry 4.0
  • Manufacturing technologies for uniquely secure low-footprint ASICs


ECTM will focus on the manufacturing technology for a multi-chip integration of a highly secure and cost-efficient root-of-trust hardware for IoT devices. Key in this integration are novel chip to chip interconnect technologies that are highly resistant against tampering and compatible with existing manufacturing technologies.

Project data

Researchers: GuoQi Zhang, Henk van Zeijl
Starting date: September 2019
Closing date: September 2021
Sponsor: Penta
Partners: NXP Semiconductors Germany GmbH (project leader), Ancud IT Beratung GmbH, AnyWi Technologies, Cloud&Heat Technologies GmbH, Delft University of Technology, Eindhoven University of Technology, ENGIE – Laborelec, Fraunhofer IIS/EAS, Sandgrain, NXP Semicond
Contact: GuoQi Zhang