Biometric systems are used for automated recognition of natural persons based on their biological characteristics and behavior, for example facial geometry, fingerprints, iris patterns, vein patterns in the hand or finger, voice patterns and handwritten signature. At first, these systems were mainly used in sovereign applications such as automated border control, forensic databases, and databases of visa applicants and asylum seekers. Increasingly, however, biometrics are finding their way into everyday commercial applications such as smartphone or PC login, access control to private or company premises or buildings, and payment transactions. The use of biometrics to unlock mobile devices is helping this science – especially fingerprint and facial recognition – to make a breakthrough in everyday life. The most prevalent biometric applications employ sensors integrated into mobile devices. Biometrics can contribute a high level of security to the respective application and offers greater convenience to users than possession- or knowledge-based authentication methods. Because biometric data are permanently associated with the individual person, however, their use entails risks as well as opportunities. The European General Data Protection Regulation (GDPR) recognizes biometric data as particularly sensitive and worthy of protection; it permits their processing only with the express consent of the data subject or on a legally regulated basis.

Our know-how

Fraunhofer Institute IGD has been conducting research and development in the field of biometrics since 1996, evaluating biometric systems and testing their security on behalf of the German Federal Office for Information Security (BSI) and the German Federal Criminal Police Office (BKA). In the course of this work, an evaluation laboratory and a demonstration center were established. We support public partners as well as industrial customers in numerous projects at national and international level in the development, evaluation and utilization of biometric procedures. Furthermore, we are actively involved in the standardization of biometric technologies under the aegis of ISO/IEC JTC 1/SC 37, understanding and helping to determine the requirements for the future application of biometric systems.


Together with scientists at the Fraunhofer Institute for Secure Information Technology (SIT), the University of Applied Sciences Darmstadt and the Technical University Darmstadt, Fraunhofer IGD is a member of ATHENE, the National Research Center for Applied Cybersecurity. ATHENE is funded by the German Federal Ministry of Education and Research (BMBF) and the Hessen Ministry of Science and the Arts (HMWK) and is located in “City of Science” Darmstadt, Germany’s premier address for cybersecurity research.

Current challenges and projects


Embedded biometrics

Modern biometric solutions require a lot of computing power, but digital systems are getting smaller and more compact in today’s world. For biometric recognition systems to work on low-end devices, efficient solutions are needed. What might these efficient solutions look like, without compromising on accuracy and thus security?


Fairness and bias

Biometric systems are increasingly finding applications in critical areas, such as border control or forensic science, where they can directly affect people’s lives. Unfortunately, studies have consistently shown that biometric systems do not necessarily behave fairly. So why are some biometric models discriminatory, and what is needed to ensure that systems are designed to be fair?


Biometric sample quality

Not every image is equally fit for use in automated face recognition. The suitability of biometric samples for recognition is also referred to as “biometric quality”. Determination of biometric quality is an essential step in the avoidance and prevention of errors. So, how exactly can the quality be established, and what are the factors that influence biometric quality?


Explainability and interpretability in biometrics

The accuracy of biometric systems is driven by current advances in deep learning. However, this progress comes with the inherent disadvantage that the internal relationships of these highly complex models are difficult to understand. But in order to build trust and security in biometric decisions, transparency is essential. So, how can highly complex models be made more explainable and interpretable?


Identification of historical figures in portrait paintings

With the passage of time, information about the person depicted in a painting often becomes forgotten. Today, we can only guess which historical person was immortalized by an artist in a painted portrait. How can modern biometric facial recognition help to recover information that was long believed to have been lost?


Detection of presentation attacks

Time and again, attempts are made to overcome biometric systems. In so-called “presentation attacks,” criminals try to spoof the relevant system with the help of artifices such as face masks, videos or fake images. So, how can such attacks be detected and unauthorized access denied? 


Face morphing

We interviewed Dr. Naser Damer about current research at the ATHENE Center into face morphing.


Study: Biometric Recognition Systems – Benefits and Obstacles in Everyday Consumer Life

Biometric Recognition Systems – Benefits and Obstacles in Everyday Consumer Life is a study based on a structured overview of biometric recognition systems currently used by consumers and very likely to be offered for use in the next five years. An online survey was conducted to determine consumer views on biometric recognition systems.


Evaluation of biometric systems for the identification of persons

Working on behalf of the Federal Criminal Police Office (Bundeskriminalamt), we evaluated four of the facial identification systems currently available on the market with regard to their recognition performance in forensic investigations.


Facial recognition where surgical masks are worn?

The ongoing COVID-19 pandemic has raised the profile of hygienic and contactless identity verification. At the same time, however, it has led to widespread wearing of face masks, which are considered essential to keep the transmission of the virus under control. The impact of mask wearing on facial recognition in a collaborative environment is a sensitive but currently neglected topic.