> For the complete documentation index, see [llms.txt](https://docs.vida.id/vida-identity-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.vida.id/vida-identity-platform/product-overview/liveness-detection.md).

# Liveness Detection

Liveness detection is an important component in the digital signature issuance process, as it helps verifying the authenticity of an individual's identity. VIDA leverages advanced AI and ML algorithms to create a passive liveness method that analyses a physically present human being and distinguishes it from a spoof artifact that may be present in a single-shot image. This method improves your conversion by having less friction in the capture experience and ensures that the person undergoing verification is physically present during the process and not using a pre-recorded image or video.

The purpose of liveness detection is to prevent fraud and impersonation, providing a higher level of security and protection to the verification process. It also ensures that only legitimate and authentic users are able to obtain digital signatures.

<figure><img src="/files/3hS6HH8RFIPJtIDed7WC" alt=""><figcaption></figcaption></figure>

## Active and Passive Liveness

VIDA supports both Active and Passive Liveness Detection to ensure secure and authentic user verification.&#x20;

[**Passive Liveness**](/vida-identity-platform/product-overview/liveness-detection/passive-liveness.md) operates in the background, analyzing selfies with advanced AI and ML techniques to confirm the image's authenticity without requiring user interaction. It generates a selfie score from 0 to 1 , basis on which the genuineness of the selfie is determined. By default, passive liveness is enabled.

[**Active Liveness**](/vida-identity-platform/product-overview/liveness-detection/active-liveness.md) involves user interaction, where the system prompts the user to perform simple actions like blinking, smiling, or moving their head. It can also include color flashing, where the screen displays changing colors to verify the user's liveness. This method ensures that the user is live and present, making it harder for attackers to spoof the system.

## Comparison between Active liveness vs. Passive liveness

<table><thead><tr><th width="177.5601806640625"></th><th width="237.41302490234375">Passive liveness</th><th>Active Liveness</th></tr></thead><tbody><tr><td><strong>Checks carried out</strong></td><td><ul><li>Image Quality check</li><li>Liveness check and Image Manipulation Check</li></ul></td><td><p>All in passive liveness, and:</p><ul><li>Face Zoom Check</li><li>Eye Blink Check</li><li>Smile Check</li><li>Head Movement Check</li></ul></td></tr><tr><td><strong>Benefit</strong></td><td><ul><li>Easy to implement and convenient for users</li><li>The photo taking process is faster</li></ul></td><td><ul><li>The level of security is higher because it involves active interactions, such as physical movements or actions, which are difficult to imitate by inanimate objects (mask/photographed paper/photographed screen) and AI-generated selfies.</li><li>Difficult to spoof with pre-recorded video due to the random nature of the directions</li><li>The use of color flash adds another layer of protection by verifying the user’s liveness through reactions to dynamic light changes, making spoofing attempts even more challenging.</li></ul></td></tr></tbody></table>

To further enhance security, VIDA incorporates an Image Manipulation Detection check as an additional layer of scrutiny. Learn more about this process on our [Image Manipulation Detection](/vida-identity-platform/product-overview/liveness-detection/image-manipulation-detection.md) page."