Towards Protecting Face Embeddings in Mobile Face Verification Scenarios

10/01/2021
by   Vedrana Krivokuća Hahn, et al.
0

This paper proposes PolyProtect, a method for protecting the sensitive face embeddings that are used to represent people's faces in neural-network-based face verification systems. PolyProtect transforms a face embedding to a more secure template, using a mapping based on multivariate polynomials parameterised by user-specific coefficients and exponents. In this work, PolyProtect is evaluated on two open-source face verification systems in a mobile application context, under the toughest threat model that assumes a fully-informed attacker with complete knowledge of the system and all its parameters. Results indicate that PolyProtect can be tuned to achieve a satisfactory trade-off between the recognition accuracy of the PolyProtected face verification system and the irreversibility of the PolyProtected templates. Furthermore, PolyProtected templates are shown to be effectively unlinkable, especially if the user-specific parameters employed in the PolyProtect mapping are selected in a non-naive manner. The evaluation is conducted using practical methodologies with tangible results, to present realistic insight into the method's robustness as a face embedding protection scheme in practice. The code to fully reproduce this work is available at: https://gitlab.idiap.ch/bob/bob.paper.polyprotect_2021.

READ FULL TEXT
research
06/14/2015

Deep Secure Encoding: An Application to Face Recognition

In this paper we present Deep Secure Encoding: a framework for secure cl...
research
04/23/2022

MLP-Hash: Protecting Face Templates via Hashing of Randomized Multi-Layer Perceptron

Applications of face recognition systems for authentication purposes are...
research
03/12/2016

Template Adaptation for Face Verification and Identification

Face recognition performance evaluation has traditionally focused on one...
research
12/05/2015

Maximum Entropy Binary Encoding for Face Template Protection

In this paper we present a framework for secure identification using dee...
research
01/22/2014

Enhancing Template Security of Face Biometrics by Using Edge Detection and Hashing

In this paper we address the issues of using edge detection techniques o...
research
10/11/2021

Biometric Template Protection for Neural-Network-based Face Recognition Systems: A Survey of Methods and Evaluation Techniques

This paper presents a survey of biometric template protection (BTP) meth...
research
10/05/2020

Common CNN-based Face Embedding Spaces are (Almost) Equivalent

CNNs are the dominant method for creating face embeddings for recognitio...

Please sign up or login with your details

Forgot password? Click here to reset