In this day and age where everything is going digital it becomes increasingly important that there is a secure and trustworthy method of identity verification. You can do it when opening a bank account online, accessing a governmental portal or signing into a safety app: it is essential to prove that it is not a picture, a mask, or a deepfake, rather than a living person in the other side of the connection. That is when active liveness detection is applicable.
Active liveness detection Liveness detection technology consists of a special subcategory considered critical to biometric security, namely active liveness detection used within facial liveness detection systems. It provides real-time validation of a user and it makes sure that it not only is valid, but that it is a live and present identity.
What is liveness detection?
A liveness detection is a biometric system that classes a real, live person and a spoof attack that utilizes photos, videos or 3D masks. It is generally applied in the case of facial recognition to avoid the fraud in the authentication process.
Liveness detection is of two main types:
Passive liveness detection: This is carried out passively in the background and does not need any user input. It also examines the natural movements and patterns to know whether the face is real.
Performance-based liveness detection: The user is asked to do something in order to prove that he/she is actually alive: e.g. they can be asked to smile, blink or turn their head.
Both techniques are equally reliable; however, active liveness mechanism is frequently more secure, since, being an interactive activity it is more–secure.
The Active Liveness Detection Work Process
In a dynamic liveness detection system, people are instructed to do some tasks during the procedure of identity verification. Such may include:
Controlled blinking
Smiling or opening of the mouth
Turing heads to either side
Tracking an object with his/her eyes
uttering a phrase, or a number at random
These prompts provide the analyses to the facial movements of the system and determine that the results are made by some human in real-time. It analyzes the regularity, spontaneity and timing of the replies to consider validity.
Active liveness detection is an efficient means of preventing identity fraud because such actions are almost impossible to re-create on photos, videos, or even with the use of advanced deepfake technology.
Pros of Active Liveness Detection
1. Greater Security Guarantee
Liveness detection attributes an additional layer of security as it involves the participation of the user. This poses a great challenge to their ability to attack the system through spoofing with the use of static or pre-captured contents.
2. Spoofing Attacks Prevention
Spoofing attacks have been developed to the level of printed photos to high-definition deepfakes. Nonetheless, the need of certain and randomized user actions severely minimizes the probability of a successful spoofing.
3. Real-Time Verification
Active liveness detection has an ability to give instnantaneous feedback and companies and organizations can make decisions to grant authorization or reject in real-time. It is particularly helpful to such areas as finance, healthcare, and the control of the border.
4. Adherence of Regulatory Standards
There are very stringent KYC (Know Your Customer) and AML (Anti-Money laundering) regulations in many industries. Using strong liveness detection features such as active liveness checks will assist in attaining the compliance standards and avoiding cases of identity thefts.
Active Liveness Detection Use Cases
Banking and Finance
Facial liveness detection has been adapted by banks in authenticating a user when opening new accounts remotely, making digital transactions as well as during loan transactions. It stops frauds and minimizes the necessity of the in-person verification.
- Telecommunication
When issuing SIM card, mobile network operators make use of liveness checks to prove that the identity coincides with official documentation.
It is also critically necessary to prove the identity of the patients and the doctors in telehealth applications. Liveness recognition acts as the security measure that hinders unauthorized people in accessing sensitive information about health.
- E- Government Services
Digital identification systems, renewing driver licenses, immigration are all areas of government using biometric systems complete with liveness detection.
Problems in Active Liveness Detection
Although it is superior, active liveness detection encounters some challenges too:
User Experience: Following prompts can be inconvenient and confusing to some users, but particularly when directions are not explicit.
Environmental Conditions: This can be altered due to poor lighting, background sound, or poor quality cameras.
Privacy issues: The users might have concerns with systems that need access to their microphone and camera.
In an attempt to address these predicaments, a large number of providers are developing AI and machine learning technology to develop more intelligent and user-friendly methods of liveness detection.
Future of Technology of Liveness Detection
There is an increasing demand of proven biometric security. Liveness detection technology, in turn, will be even more advanced with advancements in technologies such as facial recognition, detecting deep fakes, and using behavioral biometrics. Any future system has the ability to install both passive and active systems together so that it provides greater security and the least number of inconveniences to the user.
In addition, the reliability of identity verification, which is already augmented by the integration with emerging technologies and features such as 3D facial mapping, eye-tracking and voice-biometrics, can evolve further.
Final Thoughts
When in a world where the digital identity is the main tool unlocking access to the services, its safety should be put high on the agenda. One method that is reliable and safe to guarantee that the user who is trying to authenticate is not only the person he/ she is claiming but also present in real life is active liveness detection.
With the element of facial liveness detection in active approach, the business and governments can be ahead of the fraudsters, safeguard user information and make their system trustworthy. With the development of liveness detection, it is no doubt that in the future of digital interactions, liveness detection will be a central factor.
