Face recognition has proliferated as a biometric technique in recent years. With FaceID in the iPhone X, Apple has made its use more common, turning it from a futuristic technology to a common one. Other biometric recognition techniques have been surpassed by face recognition in terms of simplicity, usability, and convenience. Though the technology is weak. Non-real faces, such as those in portrait photos, can be used to trick face recognition equipment. Here comes the liveness detection to save this.
Liveness detection must be embedded into the system of face recognition technology in order to make it secure. Face recognition technology will become more widely used and secure as a result of liveness technology.
How does liveness detection work?
The capacity of a biometric system to tell the difference between a spoof and a real person—typically as part of an identity verification solution—is known as the detection of liveness. Due to its critical role in establishing a person’s authenticity, this trait is a must in the identification industry.
There are numerous techniques for determining whether someone is alive. Various bodily functions, including blood flow, precipitation, pulse, blood pressure, temperature, hippus (pupil movement), and saccade, are detected (eye movement). The use of physical reactions to external stimuli, such as eye blinking, head turns, smiles, or the timing of vocalisations. It can also be used to detect anything.
The Importance of Liveness Detection
Although advanced anti-spoofing technologies can be developed and put into use to considerably increase the level of difficulty of such assaults, biometric authentication systems can still be subject to spoofing attacks. A strong identity solution must include liveness technology to improve the biometric system’s security, dependability, and efficiency and to give more precise identity verification.
Presentation attacks (direct attacks) and indirect attacks are the two main forms of attacks on biometric systems.
Making a presentation to the sensor with the intention of getting the system to make a bad judgement is referred to as a presentation attack. A related, less formal term is “spoofing,” and liveness technology can be thought of as one of the defences against a presentation attack. To imitate a targeted identity or avoid detection are two frequently thought-of objectives of a presentation attack. Direct assaults seek to create fake biometric samples (such as speech, fingerprints, or facial photos). They are done in order to gain unauthorised access to a biometric security system’s system vulnerability point. They’ll launch an assault at the sensor level.
Identity Scams
It is important to note that no specific understanding of how the system functions are required for this type of assault (the matching algorithm used, feature extraction, feature vector format, etc). Additionally, as the attack takes place outside of the system’s digital boundaries in the analogue domain, digital protection techniques like digital signatures and watermarks cannot be applied.
Assaults could be carried out using a Trojan Horse to get around the feature extractor and matcher, respectively. These are examples of indirect attacks on the detection of liveness. Fraudsters may edit, add, or remove templates in the system database in order to access the programme. Other examples are envisioned to extract, add, or modify information from the system’s communication channels by taking advantage of any potential weak points. Contrary to direct assaults, indirect attacks require the attacker to know something about the internals of the recognition system and, in most instances, physical access to some of the application components (feature extractor, matcher, database, etc.).
Liveness As a component of identity verification:
Liveness tests are a feature of several identity verification solutions that are used during the verification process. All users can easily complete this process, which won’t stop them from finishing the authentication process. The benefits of facial recognition are immense.
Different identity verifiers use this liveness technology in different ways. Some prefer, for instance, that users write a random sentence on paper before holding it up to a liveness detector. Some subjects can find this daunting and not feel comfortable adopting this approach. When client onboarding factors in literacy rates, this strategy may be very problematic. Even having access to a pen and paper might annoy and dissuade customers. Consequently, it is crucial to take into account all facets of a product.
Conclusion
Many identification solutions will incorporate biometric technologies into their goods, but it should be a top priority to know which solution is ideal for your customers and business. It is important to use a device that incorporates liveness detection and various identity checks. Any biometric component should have liveness detection as a minimum need. Finding the most comprehensive and seamless solution is crucial. Liveness technology can be applied in a variety of inventive ways within identity verification solutions. It is crucial to delivering a user-friendly application overall and ensuring client happiness.
