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iBeta Level 2 Dataset

iBeta Level 2 Dataset

There are >25K videos tailored for iBeta level 2 certification from 150+ IDs

Check samples on Kaggle

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Introduction

iBeta Level 2 PAD is a compact training dataset for liveness detection and anti-spoofing focused on 3D mask attacks and active liveness. It includes 25k+ short multi-frame videos captured on diverse iOS and Android devices, subjects, and conditions. Covered attack types: silicone, latex, wrapped 3D paper, advanced paper, and cloth 3D masks. Ideal for training/validation and pre-certification experiments targeting iBeta Level 2

iBeta Level 2 dataset summary

  • Dataset size: 25,000+ short multi-frame videos from 150+ IDs focused on Level-2 PAD; diverse subjects across genders and ethnicities

  • Attack coverage: Silicone, Latex, Wrapped 3D Paper, Advanced Paper, Cloth 3D face masks

  • Active liveness content: Guided zoom-in / zoom-out, subtle micro-movements, natural head turns and off-axis looks; mask approach/retreat sequences

  • Capture & devices: Every attack recorded on both iOS and Android phones; varied resolutions/frame rates suitable for ML training

  • Variability: Indoor/outdoor scenes, multiple lighting levels, different backgrounds, distances, and view angles; accessories and appearance changes to increase diversity

Source and collection methodology

We captured realistic iBeta Level 2 spoofing scenarios with front-facing cameras across varied people, environments, and devices. Each clip follows an active liveness script (zoom-in/zoom-out, natural head turns/blinks) and lasts ~10 seconds

  • Recording devices

    • iOS: iPhone 14, iPhone 14 Pro, iPhone 13 Pro

    • Android: Galaxy S23, Xiaomi Redmi Note 12 Pro+, Galaxy A54, Pixel 7, Honor 70

  • Capture protocol

    • 3D mask attacks 

    • Guided zoom phases 

    • Multiple distances 

  • Environments & lighting

    • Indoor (offices, home settings) and outdoor scenes

    • Three lighting levels: low, medium, bright; mixed backgrounds

Use cases and applications

iBeta Level 2 Certification Compliance: 

  • Helps to train the models for iBeta level 2 certification tests
  • Allows pre-certification testing to assess system performance before submission

Inhouse Liveness Detection Models: 

  • Used for training and validation of anti-spoofing models
  • Enables testing of existing algorithms and identification of their vulnerabilities against spoofing attacks

See how this dataset was used to achieve iBeta Level 2 certification click here

Who is this for?

  • AI/ML teams – Train custom anti-spoofing models for security applications
  • Identity verification providers – Ensure fraud prevention in KYC & financial services
  • Financial institutions – Implement internal e-KYC solutions 

How companies achieved iBeta with us

This dataset is ideal for teams focused on liveness detection and PAD model training. It’s especially valuable for developers preparing their models for iBeta certification, as it includes a comprehensive set of spoofing scenarios required for level 1 testing

How industry leaders achieve superior liveness detection with our dataset

File format and accessibility

  • Format: Videos are optimized for compatibility with mainstream ML frameworks
  • Resolution and frame rate: Videos are high-resolution with frame rates calibrated for capturing quick and realistic mask placements, ensuring precise data for model training

Potential customisation options:

  • Filming videos attacks with targeted movements (E.g. – Zoom In / Zoom Out)
  • Filming videos attacks for you on target devices (for example, webcams)
  • Using your SDK for custom attack scenarios spoofing your ML model
  • Use RGB and USB cameras to support diverse research and testing needs

  • For two masks, video recordings are available from the back camera, capturing multiple angles (close-up, far, left, and right)

Legal & Compliance

We prioritize data privacy, ethical AI development, and regulatory compliance. Our Silicone Mask Attack Dataset is collected and processed in full accordance with global data protection standards including GDPR, ensuring legality, security, and responsible AI practices

Sample dataset

A sample version of this dataset is available on Kaggle. Leave a request for additional samples in the form below

Have a question?

We collect data from our internal team. All information is further verified by our specialists

Once your enquiry has been sent, we will contact you to discuss the details and complete the necessary paperwork. The timing of receiving the dataset depends on the specific request and additional requirements

Our unique selling point is to provide legally clean datasets to our customers. We obtain the consent from all the participants to use their data for AI model development. We are able to provide comprensive reporting on the licensing, data collection and privacy compliance of our datasets. Although there seems to be a diverse response to how to control AI development and deployment, we are able to service global customers seeking to launch global AI products.

The dataset follows iBeta testing protocols and includes diverse attack scenarios that mirror real-world spoofing attempts. It covers both passive and active liveness testing requirements with proper demographic representation and standardized capture conditions essential for certification preparation

The price depends on your specific requirements. Please submit a request to receive a free consultation

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