iBeta 3 High-Fidelity Mask Dataset

iBeta 3 High-Fidelity Rubber Mask Dataset

There are >1K videos from 5 High-Fidelity mask attacks tailored 

for iBeta level 3 certification

Check samples on Kaggle

Train for the newest iBeta Level 3 today

The iBeta 3 High-Fidelity Rubber Mask Dataset is a highly exclusive, actively expanding collection of advanced 3D rubber-mask attacks aligned with iBeta Level 3. Built for active liveness, its premium, complex masks deliver challenging sequences for training, benchmarking, and pre-certification boosting robustness and lowering false accepts

 

This is our first iBeta-3 dataset, and we’re actively expanding it so you can start preparing right now and stay ahead as the standard evolves

Dataset summary

  • Dataset Size: ~1,000 videos demonstrating spoofing attacks; 5 high-fidelity masks
  • Active Liveness Features:  Includes natural head movements and blinking to enhance training scenarios
  • Attributes: Different hairstyles, glasses and other attributes to enhance diversity
  • Variability: different locations and types of Lighting
  • This dataset can be integrated into bundles

Why this dataset?

  • Built for iBeta-3 difficulty. Active zoom-in/zoom-out prompts and high-fidelity PAD scenarios aligned to the newest certification level
  • First to market & growing. Our first iBeta-3 dataset, actively expanding—train today and stay ahead as standards evolve
  • State-of-the-art premium mask. An advanced rubber mask; we’re the first to release datasets of this kind and provide free samples

See the difference

We also have latex/silicone mask sets, but this one is far more detailed and realistic – built specifically to stress-test PAD at iBeta 3 difficulty

Source and collection methodology

The videos capture realistic spoofing conditions using different recording devices and variety of environments. Additionally, the dataset simulates common interactions like head movements and blinking, adding to its effectiveness in active liveness detection. The videos were shot using a front-facing (selfie) camera

Use cases and applications

iBeta Level 3 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

Learn the iBeta 3 context

iBeta Level 3 introduces stricter requirements: mandatory active liveness (zoom in/out), realistic high-fidelity mask attacks, and tighter APCER/BPCER/ACER limits. For implementation details and a practical checklist, see our: iBeta Level 3 guide

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 

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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