Shufti Pro Spotlight

Welcome to Shufti Pro’s latest newsletter. In it, we will feature industry experts' reviews about “ how third-party IDV providers design their algorithms to identify spoofing attacks using 2D and 3D masks.”

As long as identity verification solutions exist, cybercriminals will always find new ways to evade and bypass these fraud prevention measures. Among those techniques, face spoofing attacks prevail in which a fraudster tries to bypass a facial recognition system by presenting a 3D mask to the camera. Scammers also use AI-generated methods like deepfakes, posing the biggest challenges for facial biometric detection service providers to date.

To detect and mitigate such threats, face spoofing detection solutions such as liveness checks have emerged, backed by AI technology.

Keep reading to learn how facial biometric authentication systems can distinguish 3D or 2D objects from a smartphone camera.

Facial Biometric Trends

1. According to industry data, 3D facial recognition systems have shown significantly higher accuracy rates than traditional 2D systems, with error rates as low as 0.1%.
2. 3D depth-sensing smartphone cameras have enabled more secure and reliable face biometric authentication, with adoption rates projected to increase by 25% annually over the next 5 years.
3. The global market for facial recognition technology, including 3D and liveness detection capabilities, is expected to reach $12.92 billion by 2027, reflecting the increasing demand for robust biometric security solutions.

The Key Elements of Biometrics

Facial biometric authentication systems use various techniques to distinguish

between 3D objects, like a human face, and 2D representations, such as photos or videos from a smartphone camera. This differentiation is crucial in preventing fraudulent authentication attempts. Here are some methods employed:

Depth Sensing Technology: This is one of the key mechanisms employed by advanced facial biometric systems. Unlike traditional 2D facial recognition, which relies solely on visual patterns, these systems utilize specialized sensors such as structured light or Time-of-Flight (ToF) cameras. These sensors capture depth information, allowing the system to create a three-dimensional map of the user's face.

3D Facial Mapping: When a user attempts authentication using a smartphone camera, the biometric system actively 3D maps facial features. This involves analyzing facial landmarks' contours, shapes, and depths, including the nose, eyes, and mouth, significantly enhancing the accuracy and security of the authentication process.

Liveness Detection: Advanced facial biometric systems incorporate liveness detection mechanisms to distinguish a live face from a static image or video feed. These mechanisms assess the dynamic aspects of facial behavior, such as eye blinking, head movement, and subtle facial expressions. The system can identify and authenticate a real, present user by analyzing these live characteristics.

Texture and Reflectivity Analysis: In addition to depth sensing, facial biometric systems often analyze the texture and reflectivity of facial surfaces. Authentic human skin exhibits unique textural patterns, and how light interacts with the skin's surface provides valuable cues for differentiating between a 3D face and a 2D representation.

According to Max Williams , Founder and CEO at HeroBot , “Facial biometric authentication systems utilize a combination of depth sensing, liveness detection, texture analysis, and machine learning algorithms to distinguish between 3D and 2D objects when interacting with a smartphone camera. Collectively, these technologies enhance the security and reliability of facial recognition systems in diverse real-world scenarios.”

Biometric Authentication: A Fool-Proof Option?

In the early stages of authentication solution development, businesses struggled to differentiate between a printed headshot and real faces. But now, thanks to breakthroughs in depth sensing, machine learning, artificial intelligence, and multimodal biometrics, today's identity verification solutions are virtually spoof-proof. Modern facial authentication systems utilize multi-factor authentication techniques that leverage 2D facial recognition and 3D depth sensing technologies. Today, many fintech companies have developed 3D facial authentication solutions backed by infrared and depth-sensing sensors embedded in smartphones to create a detailed geometric map of the face. This map includes attributes like the distance between facial features that traditional 2D images cannot capture. By examining the exact depth and contours of the facial structures, advanced liveness detection algorithms can determine whether an image is of a real, living person or a printed photo or video held up to the camera. The third dimension of depth data makes it extremely difficult to spoof these systems using only 2D mediums.?

However, some systems now employ neural networks trained on extensive face datasets to conduct software-based 3D reconstruction from standard smartphone cameras for added convenience.?

Is Liveness Detection Essential for Biometric Authentication?

Sophisticated technologies like liveness detection play a crucial role. Liveness detection assesses the dynamic aspects of a face, such as subtle movements or changes in expression, ensuring that the presented image is a real, live face rather than a static photograph. Furthermore, depth-sensing technologies, like those using infrared sensors, provide additional layers of security by capturing the three-dimensional structure of the face.?

As per Dhanvin Sriram , an AI expert and a manager of Prompt Vibes, “ combining these techniques, facial biometric authentication systems can effectively discern between real, three-dimensional faces and two-dimensional representations, enhancing security in digital identity verification processes.”

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Shufti Pro’s Facial Recognition Technology

We are one of the industry-leading facial recognition solution providers backed by 3D liveness detection checks and anti-spoofing protection, capable of identifying and eliminating 2D and 3D face mask attacks while ensuring a swift and seamless onboarding experience. Our technology is equipped with advanced AI and ML algorithms, allowing customers to verify their identities using status images or videos while helping businesses ensure that clients are present during verification time.

To experience Shufti Pro’s powerful facial recognition solution, request a demo today!

Shufti Pro Insights

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Understanding Facial Identification: Face Verification vs. Face Recognition

Liveness Detection and IDV: An Overview of Biometric Facial Recognition

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