Contents
What is liveness detection and why do we need it?
Liveness detection in biometrics is the ability of a system to detect if a fingerprint or face (or other biometrics) is real (from a live person present at the point of capture) or fake (from a spoof artifact or lifeless body part).
What is biometric liveness?
Liveness detection is any technique used to detect a spoof attempt by determining whether the source of a biometric sample is a live human being or a fake representation. This is accomplished through algorithms that analyze data collected from biometric sensors to determine whether the source is live or reproduced.
What is face liveness detection?
It is an easy way to spoof face recognition systems by facial pictures such as portrait photographs. A secure system needs Liveness detection in order to guard against such spoofing. In this work, face liveness detection approaches are categorized based on the various types techniques used for liveness detection.
What is passive liveness detection?
SAFR’s passive liveness detection enhances security for face biometric authentication solutions. It adds detection and alerting capabilities when a printed photo or digital image or video is presented for identity authentication or physical access control workflows.
What spoofing means?
Spoofing is the act of disguising a communication from an unknown source as being from a known, trusted source. Spoofing can apply to emails, phone calls, and websites, or can be more technical, such as a computer spoofing an IP address, Address Resolution Protocol (ARP), or Domain Name System (DNS) server.
What is passive liveness?
Passive liveness detection technology runs in the background without users even realizing that it is occuring, so-called “security through obscurity”. It detects features of presentation attacks such as edges, texture and depth to clearly distinguish a live person’s face from an inanimate or spoofed face.
What is LivenessNet?
Face recognition is a popular concept which is commonly used in surveillance cameras at public places for security purposes. The “Face Recognition using DNN with LivenessNet” presents a face recognition method based on deep neural networks for liveness.
What does the term biometric spoofing mean?
‘Spoofing’ refers to criminally presenting artificial replications of a piece of biometric data to the biometric system in order to try and gain access. There are various different methods fraudsters use based on the biometric system in use; such as facial recognition, fingerprint scanning or iris recognition.
What is liveness detection and how does it work?
Liveness detection is considered to be a security feature that ensures that biological identifiers are from the original user and not from someone else. The traditional forms of fraud detection that are available include eye or lip movement analysis, prompted motion instructions, reflection detection in video feeds and zooming motion detection.
How is liveness check used in biometric systems?
Liveness check uses algorithms that analyze data – after they are collected from biometric scanners and readers – to verify if the source is coming from a fake representation. In essence, a liveness detection mechanism is a security feature developed to mitigate the vulnerability of biometric systems to spoofing attacks.
How is facial recognition and liveness detection used?
Recognition and Liveness Detection – Liveness detection is used in conjunction with facial recognition to detect whether someone is fraudulently impersonating another individual, which can be done either by wearing a prosthetic mask or presenting an inanimate photo or image. Facial recognition has already made its mark in the digital world.
Who are the leading players in face liveness detection?
BioID is a pioneer and the leading player in software-based face liveness detection in biometrics. Our first patent for PAD was issued in 2004. Our algorithms distinguish images or motion mimicked by photos or displays from a real person’s movement.