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README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+pretty_name: Replay Attack Dataset
+size_categories:
+- 10K<n<100K
+task_categories:
+- image-classification
+- video-classification
+language:
+- en
+tags:
+- replay-attack
+- face-anti-spoofing
+- liveness-detection
+- presentation-attack-detection
+- biometrics
+- ibeta
+- ibeta-level-1
+- computer-vision
+- spoofing-detection
+- pad
+---
+Commercial collection of 10,000+ replay attack videos covering both display-based and mobile-based replay spoofing. Captured from 2,500+ unique participants with balanced gender and ethnicity representation. Suitable for training face anti-spoofing models and preparing for iBeta PAD Level 1 certification
+
+## Dataset Summary
+Replay attacks are one of the most common presentation attack types in face biometric systems. Attackers replay a video or image of a genuine user on a screen (phone, tablet, monitor) to bypass liveness detection. A robust liveness model must see diverse replay scenarios during training
+
+This dataset combines two attack streams into a single training resource:
+
+- **Display replay attacks** - captured from a variety of screen devices (monitors, laptops, tablets) with diverse lighting conditions
+- **Mobile replay attacks** - captured across 15+ different phone models spanning low-end, mid-range, and high-end segments, including Samsung Galaxy A54, Honor 70, Google Pixel 7
+
+Both attack streams share the same capture protocol: slow camera movement, multi-angle coverage
+
+## Dataset Characteristics
+| Feature | Value |
+|---|---|
+| Total attack videos | 10,000+ |
+| Unique participants | 2,500+ |
+| Attack sub-types | Display replay + Mobile replay |
+| Mobile device coverage | 15+ phone models (incl. Galaxy A54, Honor 70, Pixel 7) |
+| Camera behavior | Slow movement, multi-angle |
+| Gender distribution | Balanced |
+| Ethnicity distribution | Balanced |
+| iBeta compliance | Level 1 (PAD) |
+
+For commercial use, production deployment, or access to the full 10,000+ video dataset, contact Axon Labs at [axonlab.ai](https://axonlab.ai/)
+
+## Use Cases
+- **Face anti-spoofing model training**: expand replay attack coverage beyond narrow academic datasets
+- **iBeta PAD Level 1 preparation**: replay attacks are a required category for iBeta Level 1 certification
+- **Cross-device generalization**: evaluate model performance across display types and phone models
+- **Benchmarking**: compare production PAD models on diverse replay scenarios
+- **Fraud prevention R&D**: detect screen replay attempts in KYC and remote onboarding systems
+
+## What Makes This Dataset Different
+- **Both attack streams in one**: most public replay datasets cover either display OR mobile, not both
+- **Realistic mobile coverage**: 15+ real phone models
+- **Commercial license available**: suitable for production deployment, not research-only
+- **Consent-based**: all subjects provided explicit consent for AI training use
+- **Scale**: 10,000+ videos is larger than most publicly available replay collections
+
+## Related Datasets from Axon Labs
+- **[iBeta Level 1 Dataset](https://axonlab.ai/dataset/ibeta-level-1-dataset/)** - full Level 1 certification package (paper + replay attacks)
+- **[iBeta Level 2 Dataset](https://axonlab.ai/dataset/ibeta-level-2-dataset/)** - 3D mask attack coverage (silicone, latex, wrapped paper)
+- **[iBeta Level 3 Dataset](https://axonlab.ai/dataset/ibeta-level-3-dataset/)** - high-fidelity mask attacks
+- **[Photo Print Attacks Dataset](https://axonlab.ai/dataset/photo-print-attacks/)** - paper photo spoofing, 3K+ individuals
+- **[Silicone Mask Dataset](https://axonlab.ai/dataset/silicone-mask-attack-data/)** - 10K+ videos from 18 silicone masks
+
+Full catalog: [axonlab.ai/datasets](https://axonlab.ai/datasets/)
+
+## About Axon Labs
+Axon Labs creates high-quality datasets for AI training, with a focus on biometric security, face recognition, and liveness detection
+
+- Website: [axonlab.ai](https://axonlab.ai/)
+- Contact: sales@axonlabs.pro
+- Full catalog: [axonlab.ai/datasets](https://axonlab.ai/datasets/)
+
+Other Axon Labs datasets on Hugging Face: [huggingface.co/AxonData](https://huggingface.co/AxonData)