Discover how Azure AI Face service uses liveness detection to verify user presence during authentication, combating fraud and improving the reliability of remote access and digital finance systems.
Table of Contents
Question
Which of the following is a use case for Azure AI Face service that provides an anti-spoofing feature that verifies if an individual is physically present when positioned in front of a camera?
A. Touchless access control
B. Liveness detection
C. Verify user identity
D. Face redaction
Answer
B. Liveness detection
Explanation
Liveness detection is a specific functionality within the Azure AI Face service that verifies the physical presence of a user in front of the camera. It helps prevent spoofing attacks where someone tries to gain access using a photo, video, or mask instead of their real face. Azure AI Face service offers AI algorithms for detecting, recognizing, and analyzing human faces in images. It has various use cases, including:
- Verification: Confirming user identity by comparing a face to a trusted image (e.g., ID card).
- Liveness detection: Verifying user presence in front of the camera (anti-spoofing).
- Touchless access control: Granting access based on facial recognition.
- Face redaction: Blurring faces in videos for privacy protection.
In line with Microsoft’s commitment to responsible AI, access to the Azure Face service is controlled to ensure its ethical and fair use. This means the service is currently limited to qualified Microsoft managed customers and partners.
While Azure Face Service offers features like face redaction, touchless access control, and user identity verification, it is important to note that these functionalities do not guarantee liveness detection (anti-spoofing):
- Face redaction: This feature blurs faces in images or videos to protect privacy, but it doesn’t confirm the physical presence of the person.
- Touchless access control: This allows access based on facial recognition, but it doesn’t inherently verify that a live person is present.
- Verifying user identity: This broader concept can be achieved through various methods, including face comparison with a trusted image. However, this process alone doesn’t necessarily ensure liveness
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