Identity verification processes often rely on static biometric data, such as fingerprints or facial features, to confirm a person’s identity. However, this approach can be vulnerable to spoofing attacks, where an attacker uses a replica of a person’s biometric data (such as a photograph or a mold of their fingerprint) to gain access to their account.
Next to that, users can use a pre-recorded video of a person to bypass the identity verification process. That’s where liveness detection comes in. It minimizes the use of synthetic identity documents as it shields off any spoofing attempts with authentication done in real-time. With liveness detection, organizations can better protect themselves from fraudsters.
In this blog, we will learn what liveness detection is, the different types, and why you should implement it to prevent identity fraud. So let’s start!
What is liveness detection?
Liveness detection is an authentication technique to verify that a person is physically present during an identity verification process and not using a fake source of a biometric sample such as a photo or a video.
Liveness detection is used to prevent identity spoofing, which is an attempt by a fraudster to gain unauthorized access to services or systems, for example, by using synthetic identities.
To make use of liveness detection, the latest AI technologies need to be in place. These technologies include:
- Deep learning algorithms are used to detect subtle differences between a live person and a photograph or a pre-recorded video.
- Computer Vision is used to detect movement, facial features, and expressions.
- Other AI (Artificial intelligence) technologies are used to detect patterns in the data and identify any anomalies that may indicate a spoofing attack.
With the AI technologies mentioned above, liveness detection provides an additional layer of security to biometric authentication and identity verification systems.
Now, let’s take a look at the different types of liveness detection.
Types of liveness detection
Liveness detection can be done by 2 different methods:
- Active liveness detection
- Passive liveness detection
Active liveness detection
Active liveness detection is a form of biometric authentication that requires a user to actively perform a specific action in order to verify their identity. Such actions can include blinking, nodding, head movements, facial expressions, or even speaking a specific phrase. With active liveness detection, the risks of synthetic identity fraud or identity spoofing in identity verification processes are significantly minimized.
Active liveness detection is becoming increasingly popular and widely used in consumer applications, such as banking and e-commerce websites, for onboarding processes or to provide a more secure way for users to access their accounts. As businesses increasingly rely on online operations, active liveness detection will become even more important in ensuring the security of systems and devices.
Passive Liveness Detection
Passive liveness detection is a method of liveness detection that does not require the user to actively perform any specific action. It is based on the idea of recognizing a person’s unique facial features such as the shape of the face, and the distance between their eyes, and comparing them to a stored image or with the picture of their ID document taken in real-time.
The difference between passive liveness detection and active liveness detection is that passive liveness uses one selfie or picture, while active liveness requires users to actively perform a specific action.
Oftentimes, passive liveness is combined with active liveness detection and other identity verification methods such as NFC to make authentication and identity verification processes more secure and robust.
But how does liveness detection work in identity verification processes? Let’s take a look.
How does liveness detection work in identity verification processes?
Liveness detection systems use a combination of hardware and software to detect if a person is present. The hardware component typically consists of a mobile phone or another device with a camera, while the software component typically consists of AI algorithms that are designed to detect changes in the person’s facial features.
But let’s zoom out a bit and see what the whole identity verification process looks like with passive liveness detection. Generally, users start the process with a smartphone by scanning their ID document, from which the software extracts the required data and the image.
Next, users take a selfie, which is then compared to the image of the ID document. If the comparison is successful, the person’s identity is verified. However, if the comparison fails, the verification process fails.
Although there are many identity verification processes that could be completed after passive liveness detection, it does not prevent users from spoofing. Hence, many companies have added actions that users have to actively perform, such as tilting their heads to the left or right, to minimize spoofing attempts. This is how active liveness detection is utilized in identity verification flows.
Liveness detection is a powerful method for preventing identity theft and spoofing, which comes with various benefits uncovered in the next section.
Why use liveness detection?
There are multiple reasons why you should use liveness detection in your identity verification process. Below, we list the main benefits:
- Greater security: Liveness detection makes sure that the person being recognized is truly there and is not using synthetic identity documents or pre-recorded videos to bypass the verification process.
- Increased precision: Liveness detection uses advanced biometric technology to accurately identify and authenticate users.
- Reduced fraud: Liveness detection helps reduce the risk of fraud and illegal access to private data and services.
- Improved user experience: Liveness detection contributes to giving the user a smoother and safer login experience, as no video call is needed for human verification.
Intelligent face liveness detection with Klippa
At Klippa, we are aware of how challenging it is to scale up and safely onboard more clients into your company. When it comes to onboarding clients online, the increase in digital customer onboarding can lead to potential safety concerns as companies must ensure their compliance with regulations for the protection of their customers.
Your client onboarding, online check-ins, and compliance checks may be simplified using Klippa’s Identity Verification. Klippa replaces the manual process of scanning, reading, and categorizing identification documents such as passports, ID cards, driver’s licenses, etc.
To protect yourself from fraud and stay compliant with Anti-Money Laundering (AML) and Know Your Customer (KYC) regulations, you can use our identity verification software, which utilizes both active and passive liveness detection. Say goodbye to spoofers!
Next to face liveness detection, you can complement your identity verification process with additional security layers:
Our solutions are available via API and SDK with proper documentation, so you can incorporate them into your own solution with ease. Wouldn’t you want to improve your business processes while safeguarding identity verification against criminal activity? With Klippa’s identity verification solution, this is possible.
All you need to do is book a demo below, where we walk you through our solution. If you want more information, you can always contact our experts.