Cyber- and Information Security for Secure Smart Societies

Cyber- and information security is the basic prerequisite for the digital transformation. Whether it is in the automation industry, automotive production, critical infrastructure or smart services, confidence in security and safety are indispensable.

Robust Artificial Intelligence and Adversarial Machine Learning

The recent years have seen dramatic improvements in artificial intelligence. The use of one common type of AI - machine learning and deep learning, where machines are fed data to learn from - is just beginning to have an impact on the region. While China has set an ambitious goal to be the world leader in AI by 2030, Artificial intelligence (AI) is still in its early stages in South-east Asia and Europe. While all ASEAN member states engage in some level of AI research and adoption, Singapore is the region's clear leader. Its AI work across multiple industries ranks Singapore ahead of international tech hot spots. With rapid progress and significant success in a wide spectrum of applications, deep learning is being applied in many safety-critical environments. At the current pace, more disruptive improvements are on the horizon.

Robust AI and Protection against Adversarial Machine Learning Attacks

The greatest danger of Artificial Intelligence is that people conclude too early that they understand and trust it. AI raises concerns that future developments may pose long-term safety and security risks. In both the short-term and the long-term, AI should be developed in a safe and beneficial manner. For instance, AI has been recently found vulnerable to well-designed input samples, called adversarial examples. Adversarial examples are imperceptible to humans but can easily fool deep neural networks in the testing and deployment stage. The vulnerability to adversarial examples becomes one of the major risks for applying deep neural networks in safety-critical environments.

Fraunhofer Singapore provides research on robust AI and attacks and defenses on adversarial examples. We are identifying areas where artificial intelligence is required to guarantee the reliability of national and industrial security processes and we are developing “application-ready” robust artificial intelligence technologies. We aim to provide optimal and robust training, inference and predictability.

Efficient Deep Fakes Identification

Deepfakes are fake video or sound recordings of humans in which the characters look and sound deceptively real. However, statements or entire interviews can be forged by any person. Freely available and politically motivated deepfakes could trigger crisis situations or political scandals. What does that mean when we can no longer trust our perception?

The technology behind it is based on a relatively new field in Deep Learning called Generative Adverserial Networks (GAN), which have significantly improved the quality and efficiency in reallistically-looking fake images and videos of human faces to replace the human in the original video. Even complete body motion can be faked to a video of a targeted human. Attackers can tamper even complex media streams very effectively to propagate false information. Because the GAN models are trained on huge datasets, it can be realistically spliced into the original video.

While those techniques work pretty well and will improve to a super-realistic fake media where almost everything is possible, the detecting of fakes is a pressing need for security, burden-of-proof and non-repudiation (of evidence) in a smart society. Fraunhofer Singapore researches on the viability and desirability of possible solutions. Through our research, we explore holistic detection and protection methods against faked visual media and deep fakes. We are working on combined methods and tools that work on physical level (e.g. verifying the lightning condition, shadow, reflection), semantical level to check the consistecy of meta-data, and on signal level (e.g. physical unclonable functions (PUFs), TPM-based data integrity protection) as well as checking for unintended information propagated by the counterfeit video material (considered as side-channel from the fake media, e.g. wrong/non eye-blinking, human pulse, etc.).

Focused Fields of Application and Domains

Security for Industrial Internet of Things / Industry 4.0

Security in Automotive and Intelligent Transportation Systems

Maritime Cyber Security

Security and Trust for Smart Services and Cyber-Physical Systems

Building a successful research and innovation partnership between Singapore, Asia and Germany.



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Contract research and development

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Test and Training

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Fraunhofer Workshop Series

Fraunhfoer Singapore offers outstanding workshops, seminars based on the research activities in collaboration with selected and prestigious partners from university and industry


Learn more about Fraunhofer Activities on Cyber Security in Singapore


Learn more about Fraunhofer Research Activities on Cyber Security in Germany