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eKYC-DF: A large-scale deepfake dataset for developing and evaluating ekyc systems

Published in IEEE Access, 2024

eKYC systems are vulnerable to advanced deepfakes, and existing datasets are not suitable for evaluating such attacks. To address this, a large-scale dataset of 228,000+ diverse fake videos with proper evaluation protocols was created specifically for eKYC systems.

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3DDGD: 3d deepfake generation and detection using 3d face meshes

Published in IEEE Access, 2025

3D face technology offers stronger security than 2D methods in biometric authentication. This study enhances 3D facial systems against deepfakes by demonstrating the superiority of 3D over 2D, creating a real/fake 3D face dataset, and developing deepfake detection models using MLP, self-attention, and TabTransformer. Results show that 3D face meshes significantly improve deepfake detection robustness.

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GFT-GCN: Privacy-Preserving 3D Face Mesh Recognition with Spectral Diffusion

Published in WACV 2026, 2026

3D face recognition provides strong security but requires protection of stored biometric templates. We propose GFT-GCN, a privacy-preserving framework that combines spectral graph learning and diffusion-based template protection to generate secure, irreversible templates. Experiments on BU-3DFE and FaceScape show high accuracy and strong resistance to reconstruction attacks, achieving a good balance between privacy and performance.

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Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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