Sustainable Security and Safety for Future Technologies

Making Future Now

MISSION

The increasing digitalization of all areas of work and life requires sustainable, secure systems and a high level of privacy protection. For this next stage of digital evolution technological breakthroughs are desired to increase the digital trust. The OpenS3 Lab is shaping the future and tomorrow’s cyber security is driven by our pioneering research.

THE OPENS3 LAB OFFER ALL OF THIS:

OPEN

Providing open high-tech security solutions for everyone

SECURE

Protection against strong adversaries in the long term

SUSTAINABLE

Building future-proof information and communication systems

SAFE

Maintain operational capability of critical systems even under attacks

 about the OpenS3 Lab  

With the OpenS3 Lab,
we will connect the academia with the industry establishing and maintaining digital trust to promote secure and safe high-tech technologies for all.

Our close cooperation with industry will significantly affect our research to tackle real-world challenges and significantly contribute to our society.
Only together we can create sustainably secure systems for the future.

Join the OpenS3 Lab: Making future now!

OUR WORK

Research Topics

Enclave Computing

Security architectures for trustworthy platforms and infrastructures

Our Projects

Internet of Things

Secure and privacy sensitive

Internet of Things

Our Projects

Machine Learning

Privacy-preserving Machine Learning and Federated Learning

Our Projects

INSIGHTS FROM OUR RESEARCH

With CURE we introduce the first security architecture that masters various challenges within enclave computing while requiring only minimal hardware modifications.




The Internet of Things is entering more and more areas of life. In the meantime, several manufacturers are producing devices with security deficiencies. Our target is to identify such security gaps autonomously, allowing the system to mitigate them effectively in a secure and sustainable manner.


Federated Learning is an attractive collaborative machine learning approach for us to apply to smart systems at large. It provides many privacy and efficiency advantages. Especially in the area of the Internet of Things, the potential for smart applications as well as smart systems is very extensive.

CONNECT WITH US


Contact us



OpenS3 Lab
Technical University of Darmstadt
Professor Ahmad-Reza Sadeghi
Pankratiusstraße 2
64289 Darmstadt