Progression in Biometric Recognition Systems and its Security

2020 ◽  
Vol 14 ◽  
Author(s):  
Ambika Annavarapu ◽  
Surekha Borra ◽  
Rohit Thanki
Keyword(s):  
Information Security ◽  
Digital Environment ◽  
Biometric Recognition ◽  
Performance Requirements ◽  
Biometric Systems ◽  
Recognition Systems ◽  
The Individual ◽  
Biometric Based Authentication

: The security of information is the major problem faced in today’s digital environment. Biometric Systems helps in achieving high–end security at precise performance requirements for various applications. This paper surveys the present multimodal and unimodal biometric based authentication systems which are in use, and their future possibilities. The authentication techniques that can identify the individual using unique features of the human such as face, fingerprint, DNA, speech and iris are discussed. Different recognition systems for new biometric traits such as voice, gait, and lip moment are also focused. This paper also focuses on information security of biometric systems and their performance requirements.

scholarly journals BIOMETRICS-A PRELIMINARY APPROACH

2017 ◽  
Vol 5 (4RACSIT) ◽  
pp. 47-52
Author(s):  
Rohini B.R. ◽  
Thippeswamy G.
Keyword(s):  
Face Recognition ◽  
Information Security ◽  
Vital Role ◽  
Physical Characteristics ◽  
Biometric Recognition ◽  
Global Security ◽  
Authentication Mechanism ◽  
Legitimate User ◽  
Recognition Systems ◽  
Face Biometrics

Authentication plays a vital role in Information security. The need for identification of legitimate user has increased in the waking concerns for global security. Biometric recognition Systems is a major tool for Authentication mechanism. Biometrics is the ability to identify and authenticate an individual using one or more of their behavioral or physical characteristics. The Study of Different Biometric Modalities gives a better understanding of Biometric Techniques. We focus our Study on Face Biometrics. This paper emphasizes on better understanding of introduction to Biometrics, Biometric Modalities and Face recognition Techniques.

scholarly journals Biometrics in Information Security

2020 ◽  
pp. 30-36
Author(s):  
German Churilin
Keyword(s):  
Information Systems ◽  
Information Security ◽  
Russian Federation ◽  
Point Of View ◽  
Access To Information ◽  
Biometric Recognition ◽  
User Identification ◽  
Biometric Data ◽  
Biometric Systems ◽  
The Russian Federation

To control the access to information systems (IS), user identification and authentication processes play an important role, which allows to identify the user by the identifier and verify its authenticity. In the most common case, these systems are based on a combination of a username and a password, i.e. the user must remember this combination. However, in recent years, the popularity of systems that use human biometric data, which is always with us and can not be forgotten or lost, has increased, which provides certain convenience for users, since they do not need to remember anything or present any identity documents. This article focuses on biometric systems from the point of view of information security. The paper addresses the issues of regulating this area by the legislation of the Russian Federation, the main threats inherent in these systems and ways to minimize them. The article discusses the use of biometric recognition in information systems as part of information security. The authors highlight the risks that may affect security and means to minimize them.

The formation of information security culture of college students

2019 ◽  
pp. 29-36
Author(s):  
I. D. Rudinskiy ◽  
D. Ya. Okolot
Keyword(s):  
College Students ◽  
Information Security ◽  
Information Society ◽  
Technical Aspect ◽  
Data Sources ◽  
Structural Components ◽  
Security Culture ◽  
The Individual ◽  
Information Security Culture ◽  
Ability And Willingness

The article discusses aspects of the formation of information security culture of college students. The relevance of the work is due to the increasing threats to the information security of the individual and society due to the rapid increase in the number of information services used. Based on this, one of the important problems of the development of the information society is the formation of a culture of information security of the individual as part of the general culture in its socio-technical aspect and as part of the professional culture of the individual. The study revealed the structural components of the phenomenon of information security culture, identified the reasons for the interest in the target group of students. It justifies the need for future mid-level specialists to form an additional universal competency that ensures the individual’s ability and willingness to recognize the need for certain information, to identify and evaluate the reliability and reliability of data sources. As a result of the study, recommendations were formulated on the basis of which a culture of information security for college students can be formed and developed and a decomposition of this process into enlarged stages is proposed. The proposals on the list of disciplines are formulated, within the framework of the study of which a culture of information security can develop. The authors believe that the recommendations developed will help future mid-level specialists to master the universal competency, consisting in the ability and willingness to recognize the need for certain information, to identify and evaluate the reliability and reliability of data sources, as well as to correctly access the necessary information and its further legitimate use, which ultimately forms a culture of information security.

Human Ear Pattern Recognition System

2017 ◽  
Vol 7 (8) ◽  
pp. 117 ◽  
Author(s):  
V. Jagan Naveen ◽  
K. Krishna Kishore ◽  
P. Rajesh Kumar
Keyword(s):  
Pattern Recognition ◽  
Expectation Maximization Algorithm ◽  
Recognition System ◽  
Modern World ◽  
Person Identification ◽  
Biometric Systems ◽  
Different Types ◽  
Recognition Systems ◽  
Human Ear ◽  
Pca Algorithm

In the modern world, human recognition systems play an important role to   improve security by reducing chances of evasion. Human ear is used for person identification .In the Empirical study on research on human ear, 10000 images are taken to find the uniqueness of the ear. Ear based system is one of the few biometric systems which can provides stable characteristics over the age. In this paper, ear images are taken from mathematical analysis of images (AMI) ear data base and the analysis is done on ear pattern recognition based on the Expectation maximization algorithm and k means algorithm.  Pattern of ears affected with different types of noises are recognized based on Principle component analysis (PCA) algorithm.

Multimodal biometric system using deep learning based on face and finger vein fusion

2021 ◽  
pp. 1-13
Author(s):  
Shikhar Tyagi ◽  
Bhavya Chawla ◽  
Rupav Jain ◽  
Smriti Srivastava
Keyword(s):  
High Performance ◽  
Recognition Accuracy ◽  
Error Rates ◽  
Facial Features ◽  
Biometric System ◽  
Deep Convolutional Neural Networks ◽  
Finger Vein ◽  
Biometric Systems ◽  
Overall Performance ◽  
Recognition Systems

Single biometric modalities like facial features and vein patterns despite being reliable characteristics show limitations that restrict them from offering high performance and robustness. Multimodal biometric systems have gained interest due to their ability to overcome the inherent limitations of the underlying single biometric modalities and generally have been shown to improve the overall performance for identification and recognition purposes. This paper proposes highly accurate and robust multimodal biometric identification as well as recognition systems based on fusion of face and finger vein modalities. The feature extraction for both face and finger vein is carried out by exploiting deep convolutional neural networks. The fusion process involves combining the extracted relevant features from the two modalities at score level. The experimental results over all considered public databases show a significant improvement in terms of identification and recognition accuracy as well as equal error rates.

Age dependency of the diabetes effects on the iris recognition systems performance evaluation results

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Mohammadreza Azimi ◽  
Seyed Ahmad Rasoulinejad ◽  
Andrzej Pacut
Keyword(s):  
Iris Recognition ◽  
Recognition Task ◽  
Aging Effect ◽  
Recognition System ◽  
Health Condition ◽  
Age Dependency ◽  
Biometric Systems ◽  
Kolmogorov Smirnov ◽  
Recognition Systems ◽  
Smirnov Test

AbstractIn this paper, we attempt to answer the questions whether iris recognition task under the influence of diabetes would be more difficult and whether the effects of diabetes and individuals’ age are uncorrelated. We hypothesized that the health condition of volunteers plays an important role in the performance of the iris recognition system. To confirm the obtained results, we reported the distribution of usable area in each subgroup to have a more comprehensive analysis of diabetes effects. There is no conducted study to investigate for which age group (young or old) the diabetes effect is more acute on the biometric results. For this purpose, we created a new database containing 1,906 samples from 509 eyes. We applied the weighted adaptive Hough ellipsopolar transform technique and contrast-adjusted Hough transform for segmentation of iris texture, along with three different encoding algorithms. To test the hypothesis related to physiological aging effect, Welches’s t-test and Kolmogorov–Smirnov test have been used to study the age-dependency of diabetes mellitus influence on the reliability of our chosen iris recognition system. Our results give some general hints related to age effect on performance of biometric systems for people with diabetes.

scholarly journals REVIEW AND ANALYSIS OF LESSONS LEARNED HANDWRITING EXPERTISE AS A WAY TO IDENTIFY PROBLEMS AND WAYS TO SOLVE THEM IN EXISTING METHODS OF HANDWRITING RESEARCH

2019 ◽  
pp. 29-44
Author(s):  
Vladlena Vyacheslavovna Lozben ◽  
Luybov Vadimovna Gajkova
Keyword(s):  
Information Security ◽  
Simulation Modeling ◽  
Lessons Learned ◽  
Comparative Characteristic ◽  
Scientific Methods ◽  
Biometric Systems ◽  
Analysis And Synthesis ◽  
The Impact ◽  
Constant Improvement ◽  
Handwriting Research

In today’s environment, information security needs constant improvement. Therefore, biometric technologies are becoming increasingly important as a key area of information protection, contributing to the widespread introduction of biometric systems across firms and organizations. Purpose: in the course of handwriting research, human participation is a prerequisite for handwriting expertise, which entails certain problems in the field of biometric expertise, the emphasis on which is contained in the article. Methodology: tools and methods are considered to reduce the impact of problems on the process of handwriting examination: popular scientific methods of phase and case analysis and synthesis; Mathematical and simulation modeling methods and tools. Results: in order to identify approaches to reducing subjectivity of expert’s conclusions, a review and analysis of existing solutions was carried out, as a result of which a comparative characteristic of approaches to solving the problem of handwriting examination was drawn up. Scope of results: the results of this study will help the organization’s leadership in information security.

scholarly journals SUPPORT OF SELF-EDUCATION IN A DISTANCE RETRAINING PROGRAM OF TUTORS

2020 ◽  
Vol 14 (4) ◽  
pp. 719-728
Author(s):  
T. A. Klimova ◽  
Keyword(s):  
Educational Environment ◽  
Educational Process ◽  
The Self ◽  
Self Determination ◽  
Educational Activity ◽  
Self Organization ◽  
Digital Environment ◽  
The Individual ◽  
Restrictive Measures

Introduction. The paper addresses the issue of support of the students involved in a fully online retraining program, which imposes special requirements on the development of the self-education ability. The study aims to establish the conditions for organizing the support of self-education in a digital educational environment. Materials and methods. The study relies on the methodology proposed by G.N. Prozumentova for reconstructing the innovative experience to analyze the reflexive text materials of the Logbook of students of the retraining program; to identify the points of stress, misunderstanding, breaks, and transitions during training; and make an analytical generalization. Results of the study. Categories of difficulties encountered by students of the program in their self-educational activity were identified, and the conditions necessary to support self-education were established. These are points of self-determination, professional trials, points of reflection, and individual educational route. Conclusion. In the context of restrictive measures during the pandemic and the transition to the online educational process, self-skills related to self-education, i.e., self-organization, independence, and self-determination, become essential. These competences are an indispensable part of the work of a tutor. However, before the tutor can support someone, they need to build these self skills themselves. The established conditions in the retraining programs will facilitate this process. At the same time, additional studies are required to reveal in more detail the individual progress of a person under these conditions for building a model for supporting the development of self-education ability, and to determine the methods for tutors to provide the support of this progress. Keywords. Self-education, self-determination, individual educational route, professional retraining, tutor, digital environment, self skills.

scholarly journals Optimized Multi-Model Biometric Based Human Authentication using Deep Neural Network

2019 ◽  
Vol 8 (3S3) ◽  
pp. 280-290
Keyword(s):  
Neural Network ◽  
Deep Neural Network ◽  
Histogram Equalization ◽  
Extraction Process ◽  
Input Image ◽  
Suggested Approach ◽  
Biometric Systems ◽  
Recognition Systems ◽  
The Right ◽  
Facial Identification

Biometrics provides greater security and usability than conventional personal authentication methods. Fingerprints, facial identification systems and voice recognition systems are the features that biometric systems can use. To improve biometric authentication, the proposed method considered that the input image is iris and fingerprint; at first, pre-processing is performed through histogram equalization for all image inputs to enhance the image quality. Then the extraction process of the feature will be performed. The suggested method uses modified Local Binary Pattern (MLBP), GLCM with orientation transformation, and DWT features next to the extracted features to be combined for feature extraction. Then the optimum function is found with the Rider Optimization Algorithm (ROA) for all MLBP, GLCM and DWT. Eventually, the approach suggested is accepted. Deep Neural Network (DNN) performs the proposed authentication process. A DNN is a multilayered artificial neural network between the layers of input and output. The DNN finds the right mathematical manipulation to turn the input into the output, whether it is an acknowledged image or not. Suggested process quality is measured in terms of reliability recognition. In the MATLAB platform, the suggested approach is implemented.

scholarly journals Biometric Systems De-Identification: Current Advancements and Future Directions

2021 ◽  
Vol 1 (3) ◽  
pp. 470-495
Author(s):  
Md Shopon ◽  
Sanjida Nasreen Tumpa ◽  
Yajurv Bhatia ◽  
K. N. Pavan Kumar ◽  
Marina L. Gavrilova
Keyword(s):  
Information Security ◽  
System Development ◽  
User Profile ◽  
Information Privacy ◽  
Biometric System ◽  
Comprehensive Overview ◽  
Future Directions ◽  
Behavioral Biometrics ◽  
Open Questions ◽  
Biometric Systems

Biometric de-identification is an emerging topic of research within the information security domain that integrates privacy considerations with biometric system development. A comprehensive overview of research in the context of authentication applications spanning physiological, behavioral, and social-behavioral biometric systems and their privacy considerations is discussed. Three categories of biometric de-identification are introduced, namely complete de-identification, auxiliary biometric preserving de-identification, and traditional biometric preserving de-identification. An overview of biometric de-identification in emerging domains such as sensor-based biometrics, social behavioral biometrics, psychological user profile identification, and aesthetic-based biometrics is presented. The article concludes with open questions and provides a rich avenue for subsequent explorations of biometric de-identification in the context of information privacy.

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