Datasets:

AxonData
/

Silicone-Mask-Attack-Dataset

Tasks:

Image Feature Extraction

Image Classification

Video Classification

Modalities:

Languages:

Size:

Tags:

silicone mask attack

biometric security

attack detection

liveness detection

Libraries:

License:

Dataset card Data Studio Files Files and versions

AxonData commited on Mar 28, 2025

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@@ -20,7 +20,7 @@ Anti spoofing dataset with Silicone 3D mask attacks (10 000 videos)
 ## Introduction
 The Silicone Mask Attack Dataset is designed to address security challenges in liveness detection systems through 3D silicone mask attacks. These presentation attacks are key for testing Passive Liveness Detection systems crucial for iBeta Level 2 certification. This dataset significantly enhances the capabilities of liveness detection models
-![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/6647e4b255f3f500dfe4546a/Xgl-C27BxR0y6H3a84pkp.jpeg)
 ## Why Silicone Mask Data?
 This dataset is crucial for companies preparing to comply with iBeta Level 2 certification which requires anti-spoofing technologies. In today's digital security landscape, the Silicone Mask Dataset serves as a critical resource for training Machine Learning (ML) models and advanced biometric techniques to detect spoofing attempts.

 ## Introduction
 The Silicone Mask Attack Dataset is designed to address security challenges in liveness detection systems through 3D silicone mask attacks. These presentation attacks are key for testing Passive Liveness Detection systems crucial for iBeta Level 2 certification. This dataset significantly enhances the capabilities of liveness detection models
+![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F20109613%2Ffa58c6f97c08537fd989c066af4d1b14%2F2025-03-26%20%2017.34.35.png?generation=1742999706709408&alt=media)
 ## Why Silicone Mask Data?
 This dataset is crucial for companies preparing to comply with iBeta Level 2 certification which requires anti-spoofing technologies. In today's digital security landscape, the Silicone Mask Dataset serves as a critical resource for training Machine Learning (ML) models and advanced biometric techniques to detect spoofing attempts.