Advances in Biometrics for Secure Human Authentication System

Biometrics ◽  
2017 ◽  
pp. 1834-1852
Author(s):  
Jagannath Mohan ◽  
Adalarasu Kanagasabai ◽  
Vetrivelan Pandu
Keyword(s):  
Recent Decade ◽  
Biometric Identification ◽  
Multimodal Biometrics ◽  
Biometric Analysis ◽  
Multifactor Authentication ◽  
Potential Alternative ◽  
Authentication System ◽  
Identification Techniques ◽  
Electrocardiogram Ecg ◽  
Pcg Signals

In the recent decade, one of our major concerns in the global technological society of information security is confirmation that a person accessing confidential information is authorized to perform so. Such mode of access is generally accomplished by a person's confirming their identity by the use of some method of authentication system. In present days, the requirement for safe security in storing individual information has been developing rapidly and among the potential alternative is implementing innovative biometric identification techniques. This chapter discusses how the advent of the 20th century has brought forth the security principles of identification and authentication in the field of biometric analysis. The chapter reviews vulnerabilities in biometric authentication and issues in system implementation. The chapter also proposes the multifactor authentication and the use of multimodal biometrics, i.e., the combination of Electrocardiogram (ECG) and Phonocardiogram (PCG) signals to enhance reliability in the authentication process.

Advances in Biometrics for Secure Human Authentication System

2016 ◽  
pp. 22-40 ◽  
Author(s):  
Jagannath Mohan ◽  
Adalarasu Kanagasabai ◽  
Vetrivelan Pandu
Keyword(s):  
Recent Decade ◽  
Biometric Identification ◽  
Multimodal Biometrics ◽  
Biometric Analysis ◽  
Multifactor Authentication ◽  
Potential Alternative ◽  
Authentication System ◽  
Identification Techniques ◽  
Electrocardiogram Ecg ◽  
Pcg Signals

In the recent decade, one of our major concerns in the global technological society of information security is confirmation that a person accessing confidential information is authorized to perform so. Such mode of access is generally accomplished by a person's confirming their identity by the use of some method of authentication system. In present days, the requirement for safe security in storing individual information has been developing rapidly and among the potential alternative is implementing innovative biometric identification techniques. This chapter discusses how the advent of the 20th century has brought forth the security principles of identification and authentication in the field of biometric analysis. The chapter reviews vulnerabilities in biometric authentication and issues in system implementation. The chapter also proposes the multifactor authentication and the use of multimodal biometrics, i.e., the combination of Electrocardiogram (ECG) and Phonocardiogram (PCG) signals to enhance reliability in the authentication process.

Real-Time ECG-Based Biometric Authentication System

2019 ◽  
pp. 275-289
Author(s):  
Jagannath Mohan ◽  
Adalarasu Kanagasabai ◽  
Vetrivelan Pandu
Keyword(s):  
Real Time ◽  
Data Storage ◽  
Personal Data ◽  
Recent Decade ◽  
Biometric Identification ◽  
Biometric Authentication ◽  
Classification Methods ◽  
Authentication System ◽  
Identification Techniques ◽  
Electrocardiogram Ecg

Security plays an important role in present day situation where identity fraud and terrorism pose a great threat. Recognizing human using computers or any artificial systems not only affords some efficient security outcomes but also facilitates human services, especially in the zone of conflict. In the recent decade, the demand for improvement in security for personal data storage has grown rapidly, and among the potential alternatives, it is one that employs innovative biometric identification techniques. Amongst these behavioral biometric techniques, the electrocardiogram (ECG) is being chosen as a physiological modality due to the uniqueness of its characteristics which integrates liveness detection, significantly preventing spoof attacks. The chapter discusses the overview of existing preprocessing, feature extraction, and classification methods for ECG-based biometric authentication. The proposed system is intended to develop applications for real-time authentication.

An optical authentication system based on encryption technique and multimodal biometrics

2013 ◽  
Vol 54 ◽  
pp. 120-127 ◽  
Author(s):  
Sheng Yuan ◽  
Tong Zhang ◽  
Xin Zhou ◽  
Xuemei Liu ◽  
Mingtang Liu
Keyword(s):  
Multimodal Biometrics ◽  
Authentication 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.

scholarly journals New Authentication Model for Multimodal Biometrics Based on Shape Features Vectors

2019 ◽  
Vol 54 (6) ◽  
Author(s):  
Sundos Abdulameer Alazawi ◽  
Huda Abdulaaliabdulbaqi ◽  
Yasmin Makki Mohialden
Keyword(s):  
High Performance ◽  
Feature Fusion ◽  
Personal Data ◽  
Rejection Rate ◽  
Shape Features ◽  
Multimodal Biometrics ◽  
Invariant Moments ◽  
Measurement And Analysis ◽  
Authentication System ◽  
Form Features

Biometrics is the science and technology dealing with the measurement and analysis of the biological features of the human body. The analysis is based on comparing the value of certain measured features with the form features in the database. Unimodal Biometric Systems have many limitations regarding precision in the identification/authentication of personal data. To accurately identify a person, a multimodal biometrics system such as combining face and fingerprint characteristic is used. Many such multi-biometrics fusion possibilities exist that can be utilized as an authentication system. In this paper, we present a new authentication system of the multimodal biometrics method for both face and fingerprint characteristics based on general shape feature fusion vectors. There are two main phases in our method: first, the fused shape features for both face and fingerprint images are extracted in accordance with central moments, and second, these features were recognized for retrieval of an authorized person using direct Euclidian distance. Experimentally, we tested about 100 shape features vectors, and observed that our method allows to improve the multimodal biometrics model when we are using the same features for two biometric images. A new method has a high-performance precision when invariant moments are used to extract shape features vectors and when similarity measurements computed based on direct Euclidean distance in the experiments are performed. We recorded False Acceptance Rate, False Rejection Rate, and Accuracy, FAR and FRR where the accuracy of the model is 91 %.

Sign in / Sign up

Export Citation Format

Share Document