Nowadays, with everything moving online, biometric verification systems have made it easier to confirm someone’s identity. These days, confirming identity through facial recognition is common when using mobile phones or joining financial services. On the other hand such technologies make it much easier for criminals to create deepfakes and use spoofing, causing serious security worries. But it is here that Active Liveness Detection proves itself valuable against fraud.
Explain what Active Liveness Detection is.
This type of biometric system confirms that the person being checked is truly there in real life and not just a picture, video or 3D mask. While passive liveness detection is always working to monitor the user, active liveness detection requires the user to interact in a recognized way. A director may ask the host to blink, smile, turn their head or react to things on the screen.
It works because a human can easily follow commands, but a person using deepfakes or photos can’t answer in real time as they do.
Deepfakes and spoofing are becoming bigger problems every day.
The use of AI and machine learning in deepfake technology helps create extremely realistic videos and sound recordings. Now, thieves use deepfakes to pretend to be someone else, take control of secure networks, alter financial operations or carry out social scams. Meanwhile, more people are using spoofing methods such as photos, videos or fake masks. If remote verification of personal identity is part of the industry, these attacks may cause significant harm.
Identity fraud is on the rise, as iProov recently found in a report and many of these attacks were aimed at online systems without liveness detection.
The Way Active Liveness Detection Is Performed
Active liveness detection software requires the user to take random actions within a short time. The tasks involved with this process could include:
- Heading the ball in a left or right direction
- Make a happy smile or raise your eyebrows.
- Blinking
- Going over a number in your mind
- Watching a moving object by moving the eyes
Such actions are examined using AI algorithms that can find depth, texture, consistency of lighting and any small movements. It is checked whether the face shown is real and live and not recorded or created by a computer.
Advantages of Using Active Liveness Detection
- Deepfake Resistance: This feature can detect and stop deepfake detection or synthetic media since it fails to react to real-time changes.
- Enhanced Recognition: Passive systems cannot match the accuracy that these systems have in spotting real users from fake ones.
- Nowadays, regulations such as GDPR, KYC and AML are promoting or requiring businesses to verify identity by including liveness detection.
- Since the prompts are created live and are always different, it becomes difficult for anyone to use pre-recorded spoofing videos.
- User Friendliness and Trust: While users get more involved in the process, active liveness detection does not change the easy-to-use nature of the system.
How Science Is Used in Many Areas
- For customers who need to join the bank remotely, get a loan approved or enter their accounts in the app.
- Telemedicine and digital health: To guarantee safe identification of patients during healthcare.
- eCommerce: To prevent someone else from using your account and making unauthorized purchases.
- Passport control, e-visas and citizen services are managed within Government & Border Security.
- For online exams and certifications, an educational institution may require you to present your identity.
Problems and Things to Consider
Active liveness detection is effective, but it does come with some issues. It is important to handle the balance between users’ safety features and how they feel when using a bank. For instance, forcing users to do many things in the app may cause frustration. We should also make sure that the site is accessible to people with disabilities.
- The use of technology is also an important aspect to keep in mind.
- Supporting the use of different devices and camera types
- Don’t allow your experiments to result in false positives or negatives.
- Rushing the wait time when processing in real time
These issues are handled by employing lightweight AI, using edge computing and generating prompts that fit well on the device or network.
The Future of Proving Who We Are
Since biometric attacks can change, we must also improve our defenses. To ensure secure identity, multi-modal biometrics will use active liveness with voice, fingerprints, behavior and device-based information for a comprehensive view.
Companies that use advanced liveness detection are ready for the next rise in fraud. They will also help build a sense of security and trust between users, partners and regulators.
Final Thoughts
Since identity is under constant threat, Active Liveness Detection has become a vital part of risk prevention. It improves facial recognition by making sure the face is moving and reacting.
Having active liveness detection in your verification process promotes safety and respect for users, as well as avoiding fraud.
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