Liveness detection is a cutting-edge technology that ensures the authenticity and veracity of an individual in a digital environment. By using advanced algorithms and techniques, liveness detection distinguishes between a live person and an attempted fraud.
This innovative solution provides an additional layer of security in processes such as digital onboarding, ensuring the integrity of processes and trust in the digital world.
Nevertheless, one of the main obstacles facing biometric recognition systems is impersonation attacks. With liveness detection, companies can confidently protect against impersonation and ensure a seamless user experience.
In the middle of this growing fraud scenario, liveness detection is vital to ensure the security of biometric-based verification processes.
Challenges in liveness detection
Sophisticated adversaries constantly devise new methods to bypass liveness detection. Adversarial attacks involve crafting specifically designed samples to deceive the system, necessitating ongoing refinement of detection algorithms to stay ahead of these challenges.
Variability in capture conditions
Liveness detection accuracy can be affected by diverse environmental factors such as lighting conditions, angle variations, and device quality.
Balancing security with user convenience poses a challenge. Implementing stringent liveness detection without causing inconvenience to users during authentication processes requires thoughtful design and optimisation.
Compliance with evolving regulatory standards, such as ISO/IEC 30107, ensures that liveness detection systems meet industry-specific security requirements, providing a benchmark for effective implementation.
Mobbeel facial liveness detection features
Our facial liveness detection technology safeguards digital identities, complying with the stringent standards outlined in ISO/IEC 30107. Our commitment to these standards reflects our dedication to providing robust, trustworthy security measures.
Versatility in methodology: active and passive liveness
Mobbeel’s liveness detection offers two distinctive methodologies:
- Active liveness detection: this method engages users in real-time actions to validate the authenticity of facial samples. Incorporating user participation, such as specific gestures or movements, confirms the presence of a live person, preventing the acceptance of static images or recorded videos as commented.
- Passive liveness detection: in contrast, passive one operates without direct user collaboration. This method uses cutting-edge algorithms and machine learning models to identify subtle features indicating the presence of a real person.
Advanced AI defence against presentation attacks
Our system harnesses the power of artificial intelligence to face impersonation attacks meticulously. It intelligently distinguishes and deflects attempted breaches from various presentation attack instruments, preventing unauthorised access to sensitive systems. It is important to mention that NIST has assessed the accuracy of our algorithms, testing the resistance to spoofing attacks.
Well-balanced security and usability
We prioritise usability with stringent security measures, designing seamless and intuitive authentication processes.
Versatility for customised solutions
Mobbeel’s facial liveness detection offers versatility in implementation, catering to diverse needs and system configurations. Our solution adapts to varying environments, whether integrated into mobile apps, gateway, or other platforms, ensuring consistent and reliable performance across different applications.
We highly recommend passive liveness detection over active one since it reduces friction and increases the process completion rate by not requiring the user’s active collaboration. Furthermore, it is an imperceptible step for the user, so fraudsters do not know when it occurs.
Use cases where include liveness detection
KYC digital onboarding with liveness detection
Facial liveness detection can verify that a user is genuine and prevent the creation of fraudulent accounts during the registration or onboarding process. Furthermore, once the technology proves the user is real, their biometric template can be stored for forthcoming authentications.
Biometric authentication with liveness detection
Facial liveness techniques can be used as an additional layer of security in authentication systems.
In terms of authentication, the possibilities are endless. Some examples where liveness can be applied are:
- User action confirmations such as transactions or account deletion: requiring users to make specific facial movements during the transaction reduces the risk of a fraudster using a photo or video to impersonate the user’s identity.
- Physical access control: security systems in buildings, facilities or wards can use facial liveness to allow access only to authorised individuals. It prevents photos or masks from being used to fool the system and ensures that only real people can enter.
- Multi-factor or two-factor authentication (2FA) for making payments.
- Password replacement.
Voice biometrics and liveness detection
Liveness detection also applies to voice authentication processes. In these processes, liveness determines whether the voice corresponds to a real individual’s voice or is an attack.
One of the most typical attacks is a replay attack, in which the voice of a legitimate person is recorded and then replayed to fool the biometric system. Nevertheless, these attacks can be detected with liveness, as they look for only specific features in an authentic voice in real time.
In addition to the replay attack, there are other presentation attacks, such as speech synthesis, where technology artificially generates a person’s voice. Despite using technology to create a voice, liveness techniques can detect the subtleties and differences between an artificially generated voice and a real voice.
The third type of attack is voice conversion, in which a person’s voice is taken and modified to sound like another person’s. Also, liveness can detect these manipulations and guarantee voice authenticity.
Feel free to reach out if you are interested in introducing anti-spoofing (liveness detection) techniques in your processes.
I am a curious mind with knowledge of laws, marketing, and business. A words alchemist, deeply in love with neuromarketing and copywriting, who helps Mobbeel to keep growing.
Discover what is face recognition
- Learn about the history of facial recognition. Origins and evolution.
- Learn how facial recognition systems work.
- See the different uses and applications.
- Understand the different implications of the technology in our society today.
- Discover the challenges in cybersecurity.
- Learn about the regulations involved in biometric processes.