Multimodal biometric identification system using fusion level of matching score level in single modal to multi-modal biometric system

2017 ◽  
Author(s):  
Chetan Jamdar ◽  
Amol Boke
Keyword(s):  
Biometric Identification ◽  
Identification System ◽  
Biometric System ◽  
Fusion Level ◽  
Matching Score

Secured Online Payment Using Biometric Identification System

2013 ◽  
Vol 824 ◽  
pp. 193-199
Author(s):  
F.O. Agbontaen ◽  
P.E. Orukpe
Keyword(s):  
Smart Card ◽  
Biometric Identification ◽  
Identification System ◽  
Biometric System ◽  
Card Reader ◽  
Online Transactions ◽  
Online Identification ◽  
Online Payment ◽  
Smart Card Reader ◽  
Made In

In this paper, we will investigate the possibilities of using highly secured online payment via biometric system in the Nigerian environment. The system proposed enables the user to purchase any product online just by slotting a biometric embedded smart card in a portable handheld smart card reader that has a fingerprint scanner touch pad and can generate different code to authenticate online transactions. While online identification and verification processes are facing frauds and undesirable incidents, this biometric payment technology offers best solution. With the help of this technology, you can ensure that transactions on purchase of any product online are made in a reliable manner. Thus, no scope is left for criminal-minded people to create loopholes in e-commerce security.

scholarly journals Multimodal Biometric Authentication for Smartphones

2021 ◽  
Vol 9 (12) ◽  
pp. 1559-1568
Author(s):  
Mrunal Pathak
Keyword(s):  
Multimodal Fusion ◽  
Biometric Identification ◽  
Identification System ◽  
Sensitive Information ◽  
Biometric Authentication ◽  
Biometric System ◽  
Multimodal Biometric System ◽  
Biometric Systems ◽  
Real Time Applications ◽  
Eye Recognition

Abstract: Smartphones have become a crucial way of storing sensitive information; therefore, the user's privacy needs to be highly secured. This can be accomplished by employing the most reliable and accurate biometric identification system available currently which is, Eye recognition. However, the unimodal eye biometric system is not able to qualify the level of acceptability, speed, and reliability needed. There are other limitations such as constrained authentication in real time applications due to noise in sensed data, spoof attacks, data quality, lack of distinctiveness, restricted amount of freedom, lack of universality and other factors. Therefore, multimodal biometric systems have come into existence in order to increase security as well as to achieve better performance.[1] This paper provides an overview of different multimodal biometric (multibiometric) systems for smartphones being employed till now and also proposes a multimodal biometric system which can possibly overcome the limitations of the current biometric systems. Keywords: Biometrics, Unimodal, Multimodal, Fusion, Multibiometric Systems

Personalized Mobile eHealth Services for Secure User Access Through a Multi Feature Biometric Framework

2019 ◽  
Vol 8 (1) ◽  
pp. 40-51 ◽  
Author(s):  
Georgios C. Manikis ◽  
Marios Spanakis ◽  
Emmanouil G. Spanakis
Keyword(s):  
User Authentication ◽  
Medical Personnel ◽  
Biometric Identification ◽  
Identification System ◽  
Biometric System ◽  
Privacy And Security ◽  
Workforce Management ◽  
User Access ◽  
Visual Characteristics ◽  
Facial Images

Humans have various features that differentiates one person from another which can be used to identify an individual for security purposes. These biometrics can authenticate or verify a person's identity and can be sorted in two classes, physiological and behavioural. In this article, the authors present their results of experimentation on publicly available facial images and the efficiency of a prototype version of SpeechXRays, a multi-modal biometric system that uses audio-visual characteristics for user authentication in eHealth platforms. Using the privacy and security mechanism provided, based on audio and video biometrics, medical personnel are able to be verified and subsequently identified for two different eHealth applications. These verified persons are then able to access control, identification, workforce management or patient record storage. In this work, the authors argue how a biometric identification system can greatly benefit healthcare, due to the increased accuracy of identification procedures.

scholarly journals Using Multiagents for Context-Aware Adaptive Biometrics

2017 ◽  
Author(s):  
Fatina Shukur
Keyword(s):  
Agent Technology ◽  
Biometric Identification ◽  
Identification System ◽  
Context Aware ◽  
Biometric System ◽  
Specific Context ◽  
Adaptive Techniques

This research is motivated by the need to design a biometric system that uses adaptive techniques relevant to a specific context to identify an individual with little or no interaction with the user. The aim of this research is to develop a framework for a context-aware adaptive multimodal biometric identification system using agent technology.

Verisoft – secure biometric identification system

2008 ◽  
pp. 83-97
Author(s):  
Georg Rock ◽  
Gunter Lassmann ◽  
Mathias Schwan ◽  
Lassaad Cheikhrouhou
Keyword(s):  
Biometric Identification ◽  
Identification System

Biometric Identification System Using Neuro and Fuzzy Computational Approaches

2016 ◽  
pp. 335-366
Author(s):  
Tripti Rani Borah ◽  
Kandarpa Kumar Sarma ◽  
Pranhari Talukdar
Keyword(s):  
Fuzzy System ◽  
Fuzzy Inference ◽  
Biometric Identification ◽  
Identification System ◽  
Inference System ◽  
Computational Approaches ◽  
Neuro Fuzzy ◽  
Actual Design ◽  
Authentication System ◽  
Numeric Data

In all authentication systems, biometric samples are regarded to be the most reliable one. Biometric samples like fingerprint, retina etc. is unique. Most commonly available biometric system prefers these samples as reliable inputs. In a biometric authentication system, the design of decision support system is critical and it determines success or failure. Here, we propose such a system based on neuro and fuzzy system. Neuro systems formulated using Artificial Neural Network learn from numeric data while fuzzy based approaches can track finite variations in the environment. Thus NFS systems formed using ANN and fuzzy system demonstrate adaptive, numeric and qualitative processing based learning. These attributes have motivated the formulation of an adaptive neuro fuzzy inference system which is used as a DSS of a biometric authenticable system. The experimental results show that the system is reliable and can be considered to be a part of an actual design.

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