Hatef Otroshi Shahreza

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Related publications (30)

On the Information in Deep Biometric Templates: from Vulnerability of Unprotected Templates to Leakage in Protected Templates

Hatef Otroshi Shahreza

Biometric recognition systems tend toward ubiquity and are widely being used in different applications for authentication purposes. Compared to conventional authentication tools, such as PIN or password, which are always in danger of being forgotten or sto ...

EPFL2024

On Measuring Linkability of Multiple Protected Biometric Templates Using Maximal Leakage

Yanina Yurina Shkel, Hatef Otroshi Shahreza

With the rapid development of biometric recognition systems, users can be simultaneously enrolled in multiple biometric recognition systems, either with a single or multiple biometric characteristics (e.g., face, voice, etc.). With such a growth of biometr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

FRCSyn Challenge atWACV 2024: Face Recognition Challenge in the Era of Synthetic Data

Alexander Carl Unnervik, Parsa Rahimi Noshanagh, Hatef Otroshi Shahreza

Despite the widespread adoption of face recognition technology around the world, and its remarkable performance on current benchmarks, there are still several challenges that must be covered in more detail. This paper offers an overview of the Face Recogni ...

IEEE2024

Multi-IVE: Privacy Enhancement of Multiple Soft-Biometrics in Face Embeddings

Sébastien Marcel, Hatef Otroshi Shahreza

This study focuses on the protection of soft-biometric attributes related to the demographic information of individuals that can be extracted from compact representations of face images, called embeddings. We consider a state-ofthe-art technology for soft- ...

IEEE COMPUTER SOC2023

SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data

Hatef Otroshi Shahreza

State-of-the-art face recognition networks are often computationally expensive and cannot be used for mobile applications. Training lightweight face recognition models also requires large identity-labeled datasets. Meanwhile, there are privacy and ethical ...

IEEE2023

Blackbox Face Reconstruction from Deep Facial Embeddings Using A Different Face Recognition Model

Hatef Otroshi Shahreza

Face recognition systems generally store features (called embeddings) extracted from each face image during the enrollment stage, and then compare the extracted embeddings with the stored embeddings during the recognition stage. In this paper, we focus on ...

New York2023

Inversion of Deep Facial Templates using Synthetic Data

Hatef Otroshi Shahreza

In this paper, we use synthetic data and propose a new method to reconstruct high-resolution face images from facial templates in a template inversion attack against face recognition systems. We use a pre-trained face generator network to generate syntheti ...

IEEE2023

Approximating Optimal Morphing Attacks using Template Inversion

Hatef Otroshi Shahreza

Recent works have demonstrated the feasibility of inverting face recognition systems, enabling to recover convincing face images using only their embeddings. We leverage such template inversion models to develop a novel type of deep morphing attack based o ...

IEEE2023

Template Inversion Attack against Face Recognition Systems using 3D Face Reconstruction

Hatef Otroshi Shahreza

Face recognition systems are increasingly being used in different applications. In such systems, some features (also known as embeddings or templates) are extracted from each face image. Then, the extracted templates are stored in the system's database dur ...

Ieee Computer Soc2023

Measuring Linkability of Protected Biometric Templates Using Maximal Leakage

Yanina Yurina Shkel, Hatef Otroshi Shahreza

As the applications of biometric recognition systems are increasing rapidly, there is a growing need to secure the sensitive data used within these systems. Considering privacy challenges in such systems, different biometric template protection (BTP) schem ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

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On Measuring Linkability of Multiple Protected Biometric Templates Using Maximal Leakage

Yanina Yurina Shkel, Hatef Otroshi Shahreza

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2024

Multi-IVE: Privacy Enhancement of Multiple Soft-Biometrics in Face Embeddings

Sébastien Marcel, Hatef Otroshi Shahreza

IEEE COMPUTER SOC2023

On the Information in Deep Biometric Templates: from Vulnerability of Unprotected Templates to Leakage in Protected Templates

Hatef Otroshi Shahreza

EPFL2024