Biometric data privacy is a growing concern as the use of biometric technologies is becoming increasingly prevalent in our daily lives. While biometric technologies can provide enhanced security and convenience, they also raise important questions about data privacy and the protection of personal information.

In this article, we will explore the concept of biometric data privacy, including the differences between recognition and authentication, and discuss best practices for complying with the General Data Protection Regulation (GDPR) or similar regulations.

By understanding the risks and benefits of biometric technologies, and following best practices for data privacy, organizations and individuals can ensure that their biometric data is used ethically and securely.

Recognition vs. Authentication

Face authentication and face recognition are two related, but distinct, technologies that are used to identify individuals based on their facial features. Both technologies have a wide range of applications, including access control, security, and personal identification. However, there are some key differences between the two that are important to understand.

Face authentication is used to verify the identity of an individual. This is typically done by comparing a live facial image of the individual to a reference image that has been previously provided. Face authentication is often used in conjunction with other forms of authentication, such as a password or an SMS code, in a multifactor authentication strategy that provides an additional layer of security.

Face recognition, on the other hand, is a process that is used to identify an individual based on their facial features. This is typically done by comparing a live facial image to a database of images and identifying the closest match. Face recognition can be used for a variety of purposes, including identifying individuals in photographs, detecting individuals in public spaces, and tracking the movements of individuals.

Biometrics data privacy and GDPR best practices

One of the key concerns surrounding face biometrics is the potential for this information to be misused or misappropriated. In addition to the risk of misuse, there are also concerns about the potential for biometric data to be used to track and monitor individuals. For example, facial recognition technology has the potential to be used to track individuals as they move through public spaces, raising questions about privacy and surveillance.

To address these concerns, the EU has implemented the General Data Protection Regulation (GDPR), which sets out strict guidelines for the collection, use, and storage of biometric data. Other countries have passed laws with similar approaches. The GDPR requires organizations to obtain explicit consent from individuals before collecting their biometric data and to provide clear and transparent information about how this data will be used. It also imposes strict rules on the storage and protection of biometric data, including requirements for secure storage and the use of encryption.

The EU Commission is also developing a regulatory framework to promote the EU as a global leader in developing secure, trustworthy, and ethical AI principles. This framework is called the AI Act and it aims to encourage businesses to develop AI solutions and give users the confidence to adopt them.

All companies commercializing biometric-based solutions in the EU should be fully compliant with both the GDRP and AI Act. There are also a few practices that organizations can follow to ensure the privacy of biometric data. These include:;

• Obtaining explicit consent from individuals before collecting their biometric data. 
• Providing clear and transparent information about how biometric data will be used.
• Regularly reviewing and updating data protection policies and procedures.
• Ensuring that biometric data is only used for the purposes for which it was collected.
• Always use the best privacy-preserving biometric technology available in the market.

Security and privacy aspects of a good biometric authentication service

There are often concerns surrounding the use of face biometrics because biometric data is potentially subject to theft and misuse. Theft of a password or security code is a serious matter that can compromise a defined set of accounts, but stealing your face is more like having your identity stolen. A multi-faceted approach is required to ensure top-notch data security.

The first security aspect used by a good biometric provider is to never store images, but rather biometric templates, which are a signature of the facial features. Biometric templates only have meaning to that specific biometric provider but not to hackers.

The second aspect is that any biometric matching is required to have an associated strong presentation attack detection algorithm, so-called liveness detection, that will only authenticate any face if it both matches the user and there is a real live person with that face in front of the device authenticating. This is where a large majority of biometric providers struggle to provide certified high-standard accuracy.

Finally, the third aspect is providing an authentication service where biometric templates are not centrally stored but rather distributed. We’ll discuss this in detail in the section below.

The role of the biometric template decentralization

Using decentralized databases, rather than storing the biometric template on a single central server, brings several advantages, particularly when it comes to security and privacy.

One of the main benefits of decentralized databases is that they are more resilient to attacks because there is no single point of failure. If one part of the network goes down, the rest of the database is still accessible. This makes decentralized databases more resistant to data breaches, hackers, and other threats.

Another advantage of decentralized databases is that they can provide more privacy and control over personal data. With it, corporations can offload the burden of data protection and give customers more control over their own data.

Overall, decentralized databases offer a number of benefits for face authentication, including improved security, privacy, and efficiency. As such, they are already playing an important role in the authentication.

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