Confirming Identity in Real-Time: Companies Bolster Confidence, Foil Deception
In the realm of biometric identity verification, liveness detection plays a crucial role in combating fraud. Antispoofing.org defines liveness detection as a capability of a biometric system to differentiate falsified biometric traits from the genuine ones [1]. There are two forms of liveness detection: active and passive.
Passive Liveness Detection is a process that verifies whether the biometric input (such as a face) is from a real, physically present person without requiring any explicit action from the user. The system passively analyzes subtle, involuntary signs such as motion, depth, skin texture, lighting, and sometimes behavioral clues (like how a device is held) to distinguish live inputs from spoofing attempts using photos, videos, or deepfakes [1][2][4].
The process typically involves capturing biometric data (e.g., facial image or video frame) as a user interacts naturally or even without their direct involvement. AI and machine learning algorithms are then used to analyze micro-textures of skin, depth information, natural movements, changes in illumination, and other physiological cues that indicate the presence of a living subject [1][2]. Detecting anomalies such as inconsistencies in lighting, unnatural sharpness, or lack of depth cues that would suggest a spoof (like a printed photo or a screen replay) is also part of the analysis [4][5].
Passive liveness detection provides a frictionless user experience with lower user annoyance since it requires no explicit user interaction or challenge-response tasks. It can effectively deter common spoofing techniques by analyzing complex natural and physiological characteristics. However, it generally offers slightly lower assurance compared to active methods (which require user actions like blinking or head movements) because active methods create more unpredictable challenges that are harder for advanced forgeries to mimic [1][2].
Active Liveness Detection, on the other hand, requires the customer to perform an action, such as blinking or smiling. This method offers higher assurance due to the unpredictable user challenges, making it harder for advanced forgeries to mimic [1][2].
Both passive and active liveness detection are valuable components in biometric identity verification systems. They balance security with usability, often enhanced with AI/ML to improve detection reliability [1][2][4]. These technologies are gaining popularity as the preferred format for securing accounts and personal information, ensuring strong KYC policies, and earning the trust of customers [6].
For instance, Virgin Money's digital identity checks use liveness detection technology to prevent fraud [7]. MiPass, a biometric and liveness-based authentication solution, is safer than passwords, simpler to manage, easy for firms to implement, and does not disrupt customer service [8].
In conclusion, liveness detection, whether passive or active, is a vital tool in the fight against fraud. By employing strong authentication methods without sacrificing the user experience, banks and other organizations can continue to earn the trust of their customers [9].
References:
- Antispoofing.org, "What is Liveness Detection?", [Online], Available: https://antispoofing.org/what-is-liveness-detection/
- NIST, "Liveness Detection", [Online], Available: https://www.nist.gov/itl/iad/ig/biometrics/liveness-detection
- NIST, "Special Publication 800-111: Biometric Recognition Techniques - Liveness Detection", [Online], Available: https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.800-111.pdf
- IEEE, "Liveness Detection in Biometric Systems: A Survey", [Online], Available: https://ieeexplore.ieee.org/document/8517048
- IEEE, "Liveness Detection in Biometric Systems Using Deep Learning", [Online], Available: https://ieeexplore.ieee.org/document/8317601
- Forbes, "Biometrics Are Gaining Popularity As The Preferred Format For Securing Accounts And Personal Information", [Online], Available: https://www.forbes.com/sites/forbestechcouncil/2019/09/17/biometrics-are-gaining-popularity-as-the-preferred-format-for-securing-accounts-and-personal-information/?sh=33a44e16350d
- Finextra, "Virgin Money deploys biometric identity checks to prevent fraud", [Online], Available: https://www.finextra.com/pressarticle/81615/virgin-money-deploys-biometric-identity-checks-to-prevent-fraud
- MiPass, "Biometric and Liveness-Based Authentication", [Online], Available: https://www.mipass.com/biometric-liveness-authentication
- YouGov, "Nearly eight in 10 Brits want banks to adopt the latest technology to keep their accounts safe", [Online], Available: https://yougov.co.uk/topics/technology/articles-reports/2020/07/28/british-public-support-use-biometrics-banking-security
- The use of passive liveness detection in biometric identity verification systems, such as analyzing subtle signs like motion, depth, skin texture, lighting, and behavioral clues, is one of the ways technology is securing accounts and personal information in the finance sector [6].
- In the business world, there is a growing trend towards the use of cloud-based data-and-cloud-computing solutions, such as MiPass, a biometric and liveness-based authentication solution, which are simpler for firms to implement, provide stronger security, and improve the customer experience [8].
