Bez kategorii – Biometriq

How to effectively detect voice-based fraud? How to distinguish a real voice from a fake one, e.g. one generated on the basis of AI? The answer is simple. This requires advanced voice biometrics tools and a number of analyses. We publish here two examples that we analyzed some time ago in our laboratory and, thanks to our proprietary algorithm, we assessed with a very high probability whether the voice is real or fake and to what extent it is consistent with the voice of a given person.

The analyzes concern:

● recognizing the voice of one of President Duda’s Russian pranksters pretending to be President Macron

● assessment of the similarity of the voices of actors Piotr Fronczewski and Filip Pławiak in the film Rojst. In the play, men play the role of the same person (Kociołek) in adulthood and youth, respectively.

We share with you the conclusions from these experiments.

Biometric comparison of the voices of Fronczewski and Pławiak.

For this purpose, we used 25 seconds of total speeches by both characters, composed of several fragments of their original speech, based on the original film soundtrack. What compliance did we achieve?
The results of the analysis showed that the actors’ biometric voices are NOT consistent. Pławiak statement vs. Fronczewski VP – only 15% agreement, Fronczewski statement vs. Pławiak VP – 11%, but interestingly, these differences are not noticed at the level of the ear. In our opinion, the voices of Pławiak and Fronczewski are almost identical. And that is ultimately what this is all about.

For both characters, gender and nationality were recognized with minimal uncertainty (score of almost 100%). An age difference between the characters was also detected, estimated at 20 years.

Analysis of the voices of Russian pranksters Vladimir Kuznetsov (Vovan) and Alexei Stolyarov (Lexus) impersonating President Macron.

In this case, we biometrically analyzed the recordings of the pranksters’ voices and compared them with the voice of the real Macron (in both Polish and English versions). We downloaded all voice samples in the form of individual recordings from the public domain on YouTube. Our goal was to confirm the effectiveness of biometric systems for this specific situation – identifying fraud.

It turned out that the voice of one of the “Lexus” pranksters was just over 50% consistent with the voice of the President of France and as much as 97% consistent with the voice of the false president. The voice of the second one – “Vovana” – showed no similarities (0%) to the fake president.

This clearly proves that thanks to biometric analysis we managed to:

●detect the fact, only after 1 minute, that a fake president was involved in the conversation
● identify the identity of the fictional president (Lexus)
● confirm that the public domain is a very good source of voice samples, which may not always be used for noble purposes
● strengthen the thesis that the most effective attacks are those using social engineering, and in this case it was the choice of the right time when the President was faced with increased stress (rocket fall).

These are just selected examples of the use of specialized biometric tools to confirm the identity of people. If implemented in the future, they may help detect voice-based abuse.

As many as 230 million stolen traditional passwords were registered despite meeting the standard requirements regarding their complexity (min. 8 characters, 1 capital letter, 1 digit, and a special character), according to Specops Breached Password Report z 2025 r. This means that the level of traditional security is insufficient and more effective protection tools are needed. Can a biometric password prove to be a more secure password? Absolutely yes!

Biometrics is one of the safer ways of logging in because it is based on biometric features of people such as face, eye pupil or voice. Biometric identifiers are unique to a given person and distinguish them from others.

The advantage of biometrics lies in its unrivaled accuracy and convenience. Unlike traditional methods such as passwords or PINs, which can be easily forgotten or stolen, biometric identifiers are inextricably linked to people. This inherent link between individuals and their biometric characteristics makes it much more difficult for unauthorized individuals to impersonate another person.

An example of secure login using biometrics is VoiceToken from BiometrIQ, a voice authentication tool that provides very strong, two-step authentication. We remind you how it is done.

When speaking words, the compliance of the read words (first level) with the pattern is verified as well as the biometric compliance of the speaker’s voice with his VoicePrint (second level).

Extremely high security is ensured by an algorithm for selecting words to be read, which reduces the possibility of guessing the sequence of words that will be displayed on the screen to almost zero. The Speech To Text (STT) mechanism combined with an innovative biometric engine guarantee high effectiveness, even in the case of attacks based on speech synthesis.

More about VoiceToken

Are you ready for changes?

We start the New Year with something interesting for fans of football and other live events. The typical, traditional ticket may soon be replaced by biometric identity verification. Research shows that nearly 50% of sports facilities have such a plan.

MLB’s ticketless “Go-Ahead Entry” system with biometric verification can reduce waiting times to enter the facility by almost 70%.

That’s why biometric authentication at sporting events could become a hit. The challenge, as always with large projects, is the financial aspect related to the costs of system implementation and investments in specialized equipment, training and tool integration. It is this aspect, according to the PYMNTS report, that may determine the implementation of biometric solutions by smaller facilities.

Go-Ahead Entry is MLB’s patented ticketless entry system using biometrics provided by NEC. The statistics come from a 2023 pilot at Citizens Bank Ballpark in Philadelphia, which showed biometric lanes move 68% faster and allow 2.5 times more people to pass than the fastest lane using physical or smartphone tickets.

We are curious how this situation will develop. Do you think this is a good idea?

More you find out here article

At the end of the year, Radio Lublin hosted an interesting program on network security. It covered, among others, issues related to digital identity, privacy and its protection, as well as the phenomenon of the rapidly growing amount of data on the Internet and the impact of this phenomenon on the development of tools, AI and the life of society. The conversation took place as part of the series “XX/XXI – a garden with forking paths”, and the participant of this inspiring conversation was Andrzej Tymecki, Managing Director of BiometrIQ. Below we share some selected statements that constitute a short summary of this meeting.

👉 The amount of data is growing incredibly fast. To illustrate the point, if we recorded the data produced in the world in one day onto DVDs and arranged them one by one, they would cover 106,000 km, which means their length would be enough to circle the Earth more than twice.

👉 The concept of privacy is constantly evolving as technology advances and new opportunities emerge. It is no longer just traditional personal data such as name, PESEL or address, but also photos and biometric features such as voice, finger touch, iris. This makes protecting privacy more and more difficult.

👉Nowadays, it is very easy to commit identity theft due to the advancement of technology and the development of AI. Protection against loss of privacy and identity theft forces caution when posting any content online.

👉The right to be forgotten, introduced into the GDPR Act in 2014, allows us to delete our data from the database.

👉Using advanced methods to protect recordings, e.g. using watermarks. may not be enough to protect against identity theft. What is needed is the good will of people on the other side (platform managers) who will verify the recordings in terms of their authenticity.

👉Procedures are a very important issue in ensuring safety. Procedures cannot be replaced by technology. Technology is supposed to support and facilitate their implementation.

👉 Data centers play a key role in terms of security, of which there are as many as 144 in Poland. The United States is undoubtedly a power in this respect, with approximately 5,300 facilities.

you can read about the program itself, as well as the entire series here

Voice payments? Why not! Nearly 50% of Poles would like to use innovative payment methods based on biometrics. Authorizing expenses by voice was indicated by 7% of Poles, by face by 8% and by iris of the eye by 9%. Payments using fingers and palms turned out to be the most popular, indicated by 20% of the respondents.

T This is according to the report “Payment references of Poles 2024” conducted this year (2024) by PolCard from Fiserv. You can read more about this study here

In our opinion, the use of biometric authorization will increase year by year, mainly due to its high effectiveness. Biometric security is simply safer than traditional ones such as passwords and is much more difficult to bypass. The main factors determining the development of biometric technologies will be:

👉 security
👉 privacy protection
👉 trust in technology and
👉 implementation costs

And You? Which method would you most like to use?

Have you ever wondered if your voice is part of your image?
If we assume that the image consists of physical features by which a person can be recognized (as stated in Wikipedia or the PWN dictionary), the voice is undoubtedly an important element of such identification.

In our opinion, the voice is not only an element of the image but also a unique biometric feature confirming identity.

What supports this fact?
Each person has a unique voice, composed of many distinct elements. Even though it may be similar to another person’s voice, its characteristics will make it unique. It allows for effective identification of the speaker not only thanks to color recognition but also biometric assessment. Using advanced biometric algorithms, we are able to determine with a very high, over 90 percent probability, whether a voice belongs to a given person and whether it is fake (generated by AI).

The language of biometrics is unfamiliar to most, even as the technology becomes ubiquitous.

People using biometric data do not necessarily know that it is “biometric data”.

A team of German researchers from the Bundeswehr University of Munich and the University of Duisburg-Essen conducted an online survey covering participants’ general understanding of physiological and behavioral biometrics and their perceived usefulness and security. Key research questions focused on literacy, perception and use, and usability and security.

Do people know what biometrics are?

What value do they see in using them?

What makes systems seem useful and secure?

The results show that although most participants were able to mention examples and claimed to use biometric technologies in their daily lives, they had difficulty with the definitions and description of biometric data. Only about 1/3 of participants gave specific examples of the use of biometrics such as fingerprints, facial recognition, ID cards and signatures.

more https://www.biometricupdate.com/202410/language-of-biometrics-is-unfamiliar-to-most-even-as-tech-becomes-ubiquitous

Today we celebrate 5 years! This is an important 5 years of experience in the field of voice biometrics, which resulted in the creation of new quality biometric solutions: an innovative VoiceToken authentication tool, which is currently covered by the EU patent procedure, and work on a voice communicator with unique functional properties that improve the safety and comfort of use, also for people with disabilities.

Because it is important to us to provide high-security solutions, we are constantly looking for new opportunities to collaborate with the best teams in the world. In 2022, we signed an agreement to implement modern biometric solutions with ID R&D from the USA, which gave us access to the biometric know-how of a major market giant.

We appreciate the annual funding from research institutions PARP and NCBiR, which proves how innovative and promising our projects are. This is nearly PLN 15 million received over these 5 years.

A big THANK YOU❤️ we installed on this day to our partners, customers and the entire BiometrIQ team for the reliability, device and heart left on the respective projects.

It is thanks to you that we are developing, creating a new, safe reality.

A few days ago, we launched a new version of the voice coherence demo, in which you can check whose voice among famous Polish athletes is closest to yours. Our list includes the names of such Olympians as Iga Świątek, Michał Kwiatkowski, Anita Włodarczyk and Hubert Hurkacz. In total, we selected as many as 20 people from 13 different disciplines.

How does the demo work?
To check who your voice is similar to, just visit the website https://demo.biometriq.pl:8443/ and read the text we have prepared, the reading time of which is only 30 seconds. During this time, we record a voice sample, which is simultaneously compared with the voices of selected 20 athletes. The results are displayed immediately in a column in the form of % convergence.

The result may show:
=> significant % convergence with only one person
=> show no convergence, then the table will remain unchanged and 0 will be shown everywhere
=> convergence with several people (this happens most often).

Remember that voices may be confusingly similar to each other, but not biometrically consistent. Conversely, they may be biometrically consistent but not audibly similar. This is because the human ear primarily perceives the intensity and tone of sound along with the location of its source, and biometric systems extract from the audio stream and analyze several features that make the analyzed voice unique.

What does biometric integrity testing give us and when is it helpful?

The algorithm used in this exercise may be used commercially in the future in systems for verifying the identity of people and detecting voice-based fraud, the so-called deepfakes. This model is constantly being developed and improved by us to be as effective and reliable as possible, which is associated with obtaining a probability of assessing the speaker’s truthfulness of over 90%.

From January 2024 We are implementing the Vesper project, which aims to create an innovative voice communicator. We informed about the project here https://biometriq.pl/en/vesper-save-voice-communication-platform-with-integration-of-biometric-services/

The aim of the first stage of the project, completed on December 31 this year, is to develop an innovative method for detecting the truthfulness of the speaker and the transmitting voice stream.
Implementing this method in the messenger will allow you to assess the compatibility of the interlocutor communicating, among others, smartphone or computer according to your expectations and prevent voice attacks.

And what we did?

1. We have developed the structure of the subsystem.

2. We have developed preliminary requirements for a methodology for detecting the veracity of the far-end voice source based on the received signal in the near-end device.

3. We have developed guidelines for measurement methodologies, taking into account the statistical significance of the results.
4. We have developed a preliminary version of research procedures taking into account the developed research scenarios for stage 1.

Scenarios and research procedures were developed taking into account the state of scientific knowledge at the time of work.

5. We have prepared a dataset for training neural networks.

6. We carried out the first training of neural networks and the selection and optimization of cost functions.
7. We performed a detailed analysis of QoE assessment methodologies in connection with qualitative objective parameters and proposed the framework of our own solution in this area.
8. We analyzed the possibilities of controlling and intervening in the audio path for mobile phones available on the market.
9. We have prepared and configured the first version of the VESPER test platform based on the Signal framework for Windows and Android.
10. We rented a DSP laboratory

11. We acquired a speech corpus for testing

12. We have purchased Voice Conversion engine licenses