iBeta Level 2 Dataset
The Dataset for successfully obtaining the iBeta Lab certificate in "Presentation Attack Detection" Level 2
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-
- Videos
- 32,300
-
- iBeta Level 2 Completion
- 100%
-
- Types of Attacks
- 6
- Facial Recognition
- iBeta
- Liveness Detection
- Security
- Anti-spoofing
- Computer Vision
-
- Videos
- 32,300
-
- iBeta Level 2 Completion
- 100%
-
- Types of Attacks
- 6
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 files | 32 300 |
| Labeling | Only technical characteristics and metadata (age, gender, ethnicity) |
| Gender | Male, Female |
| Ethnicity | Caucasian (90%), African (10%) |
| Number of attributes | 31 |
| Type of attack | Real Person, 2D mask, 2D mask with eyeholes, latex mask, wrapped 3D mask, silicone mask |
Statistics
-
- Attacks in the dataset
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- Gender of the unique people:
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- Ethnicity of the unique people:
Technical
Characteristics
| Characteristic | Data |
| Video Extensions | mp4, MOV |
| Video Resolutions | Min = 1920х1080, Max = 3840х2160 |
| Video duration | 4 second |
| Number of backgrounds | 9 |
| Video overlap | No more than 5% |
| Devices | Mi10s, Google Pixel 4, Samsung Galaxy A03s, iPhone 11, iPhone SE 2, etc. |
Industries
Finance
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Banking:
Using biometric authentication for secure access to bank accounts and transactions.
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E-commerce:
Using facial recognition technologies to prevent fraud in online purchases and authenticate users.
Security
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Access Control Integration:
Implementation of solutions based on iBeta Level 2 to enhance security levels across various sectors, including physical security and access to digital resources.
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Biometric Verification:
A method of confirming identity using unique biological traits, such as facial features, to authenticate individuals
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Cybersecurity:
Applying biometric attack detection techniques for fraud defense
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