Internet of Things (IoT) security through machine learning and data sharing (SunRISE-ECTM)
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.
|Researchers:||GuoQi Zhang, Henk van Zeijl|
|Starting date:||September 2019|
|Closing date:||September 2021|
|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|