Data recovery for a neural network-based biometric authentication scheme

2019 ◽  
Vol 10 (2) ◽  
pp. 61-74
Author(s):  
D S Bogdanov ◽  
Vladimir Olegovich Mironkin
Keyword(s):  
Neural Network ◽  
Authentication Scheme ◽  
Data Recovery ◽  
Biometric Authentication

Исследован проект стандарта защиты нейросетевых биометрических контейнеров, использующего криптографические алгоритмы. Показана несостоятельность рассмотренного совмещения парольной и нейросетевой биометрической систем защиты информации. Предложен алгоритм, позволяющий восстанавливать ключевую информацию, а также служебную информацию, определяющую процесс функционирования нейронной сети. Получен ряд численных характеристик алгоритма.

A Multiserver Biometric Authentication Scheme for TMIS using Elliptic Curve Cryptography

2016 ◽  
Vol 40 (11) ◽  
Author(s):  
Shehzad Ashraf Chaudhry ◽  
Muhammad Tawab Khan ◽  
Muhammad Khurram Khan ◽  
Taeshik Shon
Keyword(s):  
Elliptic Curve ◽  
Elliptic Curve Cryptography ◽  
Authentication Scheme ◽  
Biometric Authentication

scholarly journals Security enhanced multi-factor biometric authentication scheme using bio-hash function

PLoS ONE ◽  
2017 ◽  
Vol 12 (5) ◽  
pp. e0176250 ◽  
Author(s):  
Younsung Choi ◽  
Youngsook Lee ◽  
Jongho Moon ◽  
Dongho Won
Keyword(s):  
Hash Function ◽  
Authentication Scheme ◽  
Biometric Authentication

scholarly journals Security analysis and enhancements of an improved multi-factor biometric authentication scheme

2017 ◽  
Vol 13 (8) ◽  
pp. 155014771772430 ◽  
Author(s):  
YoHan Park ◽  
KiSung Park ◽  
KyungKeun Lee ◽  
Hwangjun Song ◽  
YoungHo Park
Keyword(s):  
User Authentication ◽  
Security Analysis ◽  
User Anonymity ◽  
Authentication Scheme ◽  
Biometric Authentication ◽  
Remote User Authentication ◽  
Dynamic Id ◽  
User Authentication Scheme ◽  
Guessing Attack ◽  
Remote User

Many remote user authentication schemes have been designed and developed to establish secure and authorized communication between a user and server over an insecure channel. By employing a secure remote user authentication scheme, a user and server can authenticate each other and utilize advanced services. In 2015, Cao and Ge demonstrated that An’s scheme is also vulnerable to several attacks and does not provide user anonymity. They also proposed an improved multi-factor biometric authentication scheme. However, we review and cryptanalyze Cao and Ge’s scheme and demonstrate that their scheme fails in correctness and providing user anonymity and is vulnerable to ID guessing attack and server masquerading attack. To overcome these drawbacks, we propose a security-improved authentication scheme that provides a dynamic ID mechanism and better security functionalities. Then, we show that our proposed scheme is secure against various attacks and prove the security of the proposed scheme using BAN Logic.

scholarly journals Person Authentication Based on the Difference of Deep Features Extracted from the Ocular and Face Regions

2019 ◽  
Author(s):  
Marcelo Vilela Vizoni ◽  
Aparecido Nilceu Marana
Keyword(s):  
Neural Network ◽  
Support Vector Machine ◽  
Convolutional Neural Network ◽  
Regions Of Interest ◽  
Support Vector ◽  
Biometric Authentication ◽  
Interesting Aspect ◽  
Fusion Strategy ◽  
Deep Cnn ◽  
The Difference

This paper presents a new method for person authentication that relies on the fusion of two biometric authentication methods based, respectively, on ocular deep features and facial deep features. In our work, the deep features are extracted from the regions of interest by using a very deep CNN (Convolutional Neural Network). Another interesting aspect of our work is that, instead of using directly the deep features as input for the authentication methods, we use the difference between the probe and gallery deep features. So, our method adopts a pairwise strategy. Support Vector Machine classifiers are trained separately for each approach. The fusion of the ocular and the facial based methods are carried out in the score level. The proposed method was assessed with a facial database taken under uncontrolled environment and reached good results. Besides, the fusion strategy proposed in this work showed better results than the results obtained by each individual method.

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