Commercial

iBeta Level 1 Dataset

The dataset supports biometric testing against presentation attacks and ensures compliance with iBeta Level 1 certification requirements for liveness detection and security quality assurance

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  • Videos
    35, 800
  • iBeta Level 1 Completion
    100%
  • Type of Attacks
    8
  • Facial Recognition
  • iBeta
  • Liveness Detection
  • Security
  • Anti-spoofing
  • Computer Vision
  • Videos
    35, 800
  • iBeta Level 1 Completion
    100%
  • Type of Attacks
    8

Dataset Info

Characteristic Data
Description Videos of people for training algorithms to detect attempts to hack biometric systems.
Data types Video
Tasks Face recognition, Computer Vision
Total number of Videos 35,800
Number of actor 50
Labeling Only technical characteristics and metadata (age, gender, ethnicity)
Gender Male, Female
Ethnicity Caucasian (60%), Asian (20%), African (20%)
Features Bald, beard-mustache, makeup, scar, piercing, no features
Age 18-29 (44%), 30-49 (50%), 50+ (6%)
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Case Description

Developed to satisfy the laboratory’s requirements

Successfully used to get iBeta Level 1 certificate

Ready-to-use for training liveness detection systems

100% accuracy, without type 1 and type 2 errors

Statistics

Distribution by gender
Distribution by ethnicity
Distribution by age

Technical
Characteristics

Characteristic Data
Video extensions mp4, MOV
Video Resolutions Min = 1920х1080, Max = 3840х2160
Video duration 5 second
Number of backgrounds 10
Devices Samsung Galaxy A53, OPPO A18, iPhone 14, Apple iPad 10.2 and etc.
Source and collection methodology: Data was collected by Unidata team in a rented studio.

FAQs

What is included in this dataset?
The iBeta Level 1 Video Attacks dataset includes 35,800 videos of 50 actors, curated for biometrics testing and attack detection in biometric systems. Videos cover face recognition and computer vision tasks, labeled with technical characteristics and metadata such as age, gender, and ethnicity. Actors exhibit diverse features including bald, beard-mustache, makeup, scar, and piercing, across multiple backgrounds and high-resolution video formats (mp4, MOV). This dataset supports iBeta certification, liveness detection, and research in biometric security, authentication solutions, and digital identity protection.
Is this a real-world dataset or synthetic data?
iBeta Level 1 Dataset consists of real-world data captured from 50 actors, designed for biometrics testing, liveness detection, and attack detection in biometric systems. It supports face recognition, authentication solutions, and biometric evaluations, providing realistic scenarios for presentation attacks and spoofing attempts in research in the biometrics industry.
How are the Unidata datasets licensed?
Unidata datasets are provided under a dual model: free dataset samples are available for testing and evaluation, while access to the full dataset is granted only upon purchase.
How are Unidata datasets stored?
Unidata stores all datasets securely on AWS cloud infrastructure, ensuring high availability and scalability. Our storage and management practices are aligned with ISO 27001 and ISO 27701 standards, which guarantee compliance with internationally recognized information security and privacy management requirements. This approach provides a secure, reliable, and privacy-focused environment for handling data.
Can I request a sample of this dataset before purchasing?
Yes. Unidata offers dataset samples so you can evaluate video quality, technical characteristics, and scenario diversity, including actor features, backgrounds, and resolutions, for biometrics testing, face recognition, and attack detection before making a purchase decision.
Does our iBeta Level 1 Dataset meet SLA compliance standards?
Yes. Unidata iBeta Level 1 Dataset is fully SLA compliant, meeting strict standards for security, reliability, and biometric data integrity. It aligns with iBeta certification requirements, supporting biometric evaluations, liveness detection, and presentation attacks research.
How long does it take to receive the dataset?
Once you submit a request, we will reach out to you to review the details and complete the necessary documents. After signing and payment, the iBeta Level 1 Dataset will be delivered within 3–10 days, allowing you to start biometrics testing, face recognition, liveness detection, and attack detection in biometric systems promptly.
Do Unidata datasets follow GDPR or other data privacy regulations?
Yes. All datasets are curated in compliance with GDPR and applicable data protection laws. Data is collected from legally permissible sources to ensure ethical and lawful usage.
Still have questions about using Unidata datasets? Read our user-guides

Dataset Use Cases

  • Financial Services

    Stronger Protection Against Identity Fraud

    Banks and fintech companies use the iBeta Level 1 Certification Dataset to improve biometric authentication systems. By testing recognition systems against presentation attacks, this biometric dataset helps institutions detect spoofing attempts before they compromise digital identity solutions. The liveness detection dataset supports secure transactions, strengthens trust in mobile banking, and aligns with certification processes for accredited biometrics.

  • Biometrics and Technology Industry

    Improving Biometric Security Solutions

    Technology companies and research teams rely on the iBeta Level 1 dataset for developing and validating recognition systems. The biometric data it provides allows testing capabilities for attack detection, liveness detection, and authentication solutions. By supporting iBeta certification requirements, the dataset helps refine recognition technology, reduce vulnerabilities in biometric systems, and drive innovation across the global biometrics industry.

  • Healthcare

    Controlled Access to Sensitive Records

    In healthcare, the iBeta dataset is applied to safeguard electronic health records and restrict access to authorized personnel. Through independent testing and biometrics evaluations, authentication systems learn to detect presentation attacks in real scenarios. This enhances patient privacy, improves compliance with quality assurance standards, and ensures biometric technology can reliably protect sensitive medical information.

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