Biometric Spoofing and Anti-Spoofing

2017 ◽  
pp. 121-139
Author(s):  
Zahid Akhtar
Keyword(s):  
Large Scale ◽  
Security Requirements ◽  
Security Systems ◽  
Comprehensive Overview ◽  
Research Directions ◽  
Person Recognition ◽  
Biometric Systems ◽  
Prime Objective ◽  
Recognition Systems ◽  
Multimodal Biometric Systems

The demand for reliable and robust person recognition systems has expanded due to intense security requirements in today's highly intertwined network society. The advantages of biometrics over traditional security systems have triggered large-scale deployment of biometrics as an authentic technique to determine the identity of an individual. The prime objective of such methods is to assure that the systems are only accessed by genuine users. Since, biometric traits are overt, leading thus to a threat of them being captured, copied, and forged. Numerous techniques have been developed over the years for biometric spoofing and anti-spoofing. The goal of this chapter is to provide a comprehensive overview on works in the field of spoofing and anti-spoofing with special attention to three mainly accepted biometric traits (i.e., fingerprint, face and iris) and multimodal biometric systems. We also present the key challenges, major issues and point out some of the salient and useful research directions.

scholarly journals Technologies to Overcome Spoofing Attack in Facial Recognition

2019 ◽  
Vol 8 (2S4) ◽  
pp. 36-41
Keyword(s):  
Facial Recognition ◽  
Real Life ◽  
Future Research ◽  
Biometric System ◽  
Security Systems ◽  
Research Directions ◽  
Biometric Systems ◽  
Future Research Directions ◽  
Behavioral Attributes ◽  
Compare And Contrast

The identification technologies used nowadays consists of biometrics as an essential component. The basic use of a conventional biometric system is to identify the authenticity of an individual through its physical as well as behavioral attributes, which is considered as one of the most suitable method to secure confidentiality of data. Though the security of these systems is stringent to breach, still it does consists of vulnerabilities due to various reasons. One of the major threats the current biometric system possess are the spoofing attacks. Spoofing attacks are difficult to conquer due to the fact that a person tries to masquerade as others in order to gain unauthorized access to the security systems. This is one of the biggest problem concerning the integrity of the biometric system. The study of spoofing attacks has gained interest of various researchers in the field of computer science, still there are aspects which needs greater attention in order to achieve a plausible solution. The study is based on the current biometric systems in order to compare and contrast the existing technology used in facial recognition. A detailed review of the existing anti – spoofing methods will be taken into account to discuss the future research directions. Thus, the work will focus on threats to the current security systems, with an aim to analyse the possible countermeasures, and its applications in real life scenarios.

Multi-Modal Biometrics Systems: Concepts, Strengths, Challenges and Solutions

2021 ◽  
Vol 10 (3) ◽  
pp. 1827-1831
Keyword(s):  
Computer Security ◽  
Multimodal Biometrics ◽  
Security Systems ◽  
Biometric Technology ◽  
Biometric Systems ◽  
Password Based Authentication ◽  
Multimodal Biometric Systems

Authentication is a very important aspect of computer security. Most systems employ strategies such as Password-based authentication, Multi-factor authentication, Certificate based authentication which are accompanied with a lot ofchallenges. To address this issue, most security systems have introduced the use of biometrics for authentication. Unimodal biometrics systems have many limitations regarding performance and accuracy. The use of Multimodal biometrics systems for authentication is recently attracting the attention of researchers due to its capacity to overcome most of the drawbacks of Unimodal biometric systems. This paper focuses on the use of biometric technology for authentication. The strengths of multimodal biometric systems, together with the challenges of multimodal biometric systems are presented. The paper also suggests solutions to the challenges of multimodal biometric systems.

YÜZ TANIMA TABANLI DUYURU SİSTEMİ TASARIMI VE KULLANILABİLİRLİĞİ

2021 ◽  
Vol 8 (16) ◽  
pp. 21-35
Author(s):  
Berk YILMAZER ◽  
Serdar SOLAK
Keyword(s):  
Cloud Computing ◽  
Face Recognition ◽  
Large Scale ◽  
Facial Recognition ◽  
Experimental Studies ◽  
Shopping Mall ◽  
Person Recognition ◽  
Additional Equipment ◽  
Recognition Systems ◽  
The Cost

The rapid developments in technology have an increasing impact and use on biometric person recognition systems. Facial recognition-based systems, one of the biometric person recognition systems, have been widely used in recent years thanks to their easy implementation, fast integration and simple usage as they do not require any additional equipment. Especially the widespread use of computer vision and cloud-computing based applications, smart face recognition systems have become an indispensable part of our lives in recent years. The use of these systems, which have become widespread in security, health, education, military, shopping mall and industrial areas, has increased more during the pandemic period. Institutions and organizations do not want to allocate time and cost to write their own software for face recognition based systems. The services offered by major cloud computing providers can be used to solve this problem. In this context, the article presents a smart announcement system design using cloud computing based face recognition technology. In the past, making an announcement has been seen as a difficult task. It was thought to be a time consuming task, both because of the cost of printing and because all the operations had to be repeated when there were changes in the announcement. Today, signs have left their places to digital screens. It will especially ensure that announcements, warnings, promotions, and notifications are performed effectively at the developed system for large scale institutions, organizations, factories, universities, shopping malls and health institutions. Facial recognition based smart announcement system detects features such as person recognition, gender, and age estimation at a rate of 100% and displays personal announcements according to their priority status. In addition, according to the experimental studies, it was observed that the person recognition and the presentation of the announcements on the screen took an average of 1.3 seconds. According to the announcement system survey, 85% of those who use the system stated that it is useful and user-friendly.

scholarly journals Biometric Technologies in Recognition Systems: A Survey

2019 ◽  
Vol 24 (6) ◽  
pp. 132
Author(s):  
Shihab A. Shawkat1 ◽  
Raya N. Ismail2
Keyword(s):  
Identity Management ◽  
Personal Attributes ◽  
Behavioral Characteristics ◽  
Human Society ◽  
Biometric System ◽  
Comprehensive Overview ◽  
Biometric Systems ◽  
Identity Management Systems ◽  
Recognition Systems ◽  
Hand Geometry

The ability to recognize people uniquely and to associate personal attributes such as name and nationality with them has been very important to the fabric of human society. Nowadays, modern societies have an explosion in population growth and increased mobility which necessitated building advanced identity management systems for recording and maintaining people’s identities. In the last decades, biometrics has played an important role in recognizing people instead of traditional ways such as passwords and keys which can be forgotten or be stolen. Biometric systems employ physiological and/or behavioral characteristics of people to verify their identities. There are different biometric modalities that can be used to recognize people such as fingerprints, face, hand geometry, voice, iris, signature, etc. In this paper, a comprehensive overview have been provided on the major issues of biometric systems including general biometric system architecture, major biometric traits, biometric systems performance, and some relevant works.   http://dx.doi.org/10.25130/tjps.24.2019.120

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.

Dehydroepiandrosterone (DHEA) and its Sulphate (DHEAS) in Alzheimer’s Disease

2020 ◽  
Vol 17 (2) ◽  
pp. 141-157 ◽  
Author(s):  
Dubravka S. Strac ◽  
Marcela Konjevod ◽  
Matea N. Perkovic ◽  
Lucija Tudor ◽  
Gordana N. Erjavec ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Large Scale ◽  
Therapeutic Potential ◽  
Relevant Literature ◽  
Comprehensive Overview ◽  
Brain Functions ◽  
Specific Effects ◽  
And Behavior

Background: Neurosteroids Dehydroepiandrosterone (DHEA) and Dehydroepiandrosterone Sulphate (DHEAS) are involved in many important brain functions, including neuronal plasticity and survival, cognition and behavior, demonstrating preventive and therapeutic potential in different neuropsychiatric and neurodegenerative disorders, including Alzheimer’s disease. Objective: The aim of the article was to provide a comprehensive overview of the literature on the involvement of DHEA and DHEAS in Alzheimer’s disease. Method: PubMed and MEDLINE databases were searched for relevant literature. The articles were selected considering their titles and abstracts. In the selected full texts, lists of references were searched manually for additional articles. Results: We performed a systematic review of the studies investigating the role of DHEA and DHEAS in various in vitro and animal models, as well as in patients with Alzheimer’s disease, and provided a comprehensive discussion on their potential preventive and therapeutic applications. Conclusion: Despite mixed results, the findings of various preclinical studies are generally supportive of the involvement of DHEA and DHEAS in the pathophysiology of Alzheimer’s disease, showing some promise for potential benefits of these neurosteroids in the prevention and treatment. However, so far small clinical trials brought little evidence to support their therapy in AD. Therefore, large-scale human studies are needed to elucidate the specific effects of DHEA and DHEAS and their mechanisms of action, prior to their applications in clinical practice.

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.

Performance of Multimodal Biometric Systems Using Face and Fingerprints (Short Survey)

2021 ◽  
Author(s):  
Mohamed Abdul-Al ◽  
George Kumi Kyeremeh ◽  
Naser Ojaroudi Parchin ◽  
Raed A Abd-Alhameed ◽  
Rami Qahwaji ◽  
...  
Keyword(s):  
Short Survey ◽  
Biometric Systems ◽  
Multimodal Biometric Systems
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