4. Enhancing biometric processing

2018 ◽  
pp. 74-89
Author(s):  
Michael Fairhurst
Keyword(s):  
System Performance ◽  
Data Integrity ◽  
Practical Situation ◽  
Biometric Data ◽  
Soft Biometrics ◽  
Multimodal Systems ◽  
Biometric Systems ◽  
Main Ideas

‘Enhancing biometric processing’ explores how the field of biometrics is developing, and the main ideas promoting the improvement of the accuracy, reliability, and effectiveness of biometric systems. It is unlikely that any individual biometric modality operating alone will completely meet all the desirable criteria for a given task, especially when the variety of issues that are needed are considered in any practical situation. To improve system performance different systems can be used such as adding extra power using a multiclassifier configuration, increasing flexibility using multimodal systems, and using soft biometrics as additional identity evidence. Resistance to ‘spoofing’ attacks, biometric data integrity, and extending the application domains for biometrics-based processing are also considered.

scholarly journals An evaluation of a three-modal hand-based database to forensic-based gender recognition

2019 ◽  
Author(s):  
Juliana De A. S. M. ◽  
Márjory Da Costa-Abreu
Keyword(s):  
The Other ◽  
Gender Recognition ◽  
Performance Information ◽  
Biometric Data ◽  
Soft Biometrics ◽  
Biometric Systems ◽  
Handwritten Signature

In recent years, behavioural soft-biometrics have been widely used to improve biometric systems performance. Information like gender, age and ethnicity can be obtained from more than one behavioural modality. In this paper, we propose a multimodal hand-based behavioural database for gender recognition. Thus, our goal in this paper is to evaluate the performance of the multimodal database. For this, the experiment was realised with 76 users and was collected keyboard dynamics, touchscreen dynamics and handwritten signature data. Our approach consists of compare two-modal and one-modal modalities of the biometric data with the multimodal database. Traditional and new classifiers were used and the statistical Kruskal-Wallis to analyse the accuracy of the databases. The results showed that the multimodal database outperforms the other databases.

Systematic Error Analysis for the Enhancement of Biometric Systems Using Soft Biometrics

2012 ◽  
Vol 19 (12) ◽  
pp. 833-836 ◽  
Author(s):  
Anastasios Drosou ◽  
D. Tzovaras ◽  
K. Moustakas ◽  
M. Petrou
Keyword(s):  
Error Analysis ◽  
Systematic Error ◽  
Soft Biometrics ◽  
Biometric Systems

Verification of Multimodal Biometric

2018 ◽  
pp. 147-193
Author(s):  
Shashidhara H. R. ◽  
Siddesh G. K.
Keyword(s):  
Multimodal Systems ◽  
Biometric Systems ◽  
Physical Traits ◽  
Reliability And Robustness ◽  
Secure Authentication ◽  
Physical Trait ◽  
Multimodal Biometric Systems

Authenticating the identity of an individual has become an important aspect of many organizations. The reasons being to secure authentication process, to perform automated attendance, or to provide bill payments. This need of providing automated authentication has led to concerns in the security and robustness of such biometric systems. Currently, many biometric systems that are organizations are unimodal, which means that use single physical trait to perform authentication. But, these unimodal systems suffer from many drawbacks. These drawbacks can be overcome by designing multimodal systems which use multiple physical traits to perform authentication. They increase reliability and robustness of the systems. In this chapter, analysis and comparison of multimodal biometric systems is proposed for three physical traits like iris, finger, and palm. All these traits are treated independently, and feature of these traits are extracted using two algorithms separately.

Performance Measures for Multimodal Transportation Systems

1996 ◽  
Vol 1518 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Richard H. Pratt ◽  
Timothy J. Lomax
Keyword(s):  
Land Use ◽  
Performance Measurement ◽  
Travel Time ◽  
Performance Measures ◽  
System Performance ◽  
Transportation Systems ◽  
Regional Networks ◽  
Multimodal Transportation ◽  
Decision Context ◽  
Multimodal Systems

Transportation systems analyses have been evolving as the decision context for improvement projects and programs has changed. The increased emphasis on the movement of persons and goods, and a recognition of the importance of system performance measures that address the needs and interests of the audiences for mobility information, will result in a very different set of procedures for evaluating transportation and land use infrastructure and policies. Some of the key underlying concerns of performance measurement for multimodal systems are presented. Definitions are included for congestion, mobility, and accessibility that are used to guide the development of performance measures. Travel time–based measures are seen as the most readily understandable quantities, and examples are used to show how mobility can be measured for locations, corridors, transit analyses, and regional networks.

Overview

2011 ◽  
pp. 1-23
Author(s):  
David Zhang ◽  
Fengxi Song ◽  
Yong Xu ◽  
Zhizhen Liang
Keyword(s):  
Pattern Recognition ◽  
Recognition Performance ◽  
Recognition System ◽  
Biometric System ◽  
Biometric Recognition ◽  
Biometric Data ◽  
Pattern Recognition System ◽  
Biometric Systems ◽  
History Of

A biometric system can be regarded as a pattern recognition system. In this chapter, we discuss two advanced pattern recognition technologies for biometric recognition, biometric data discrimination and multi-biometrics, to enhance the recognition performance of biometric systems. In Section 1.1, we discuss the necessity, importance, and applications of biometric recognition technology. A brief introduction of main biometric recognition technologies are presented in Section 1.2. In Section 1.3, we describe two advanced biometric recognition technologies, biometric data discrimination and multi-biometric technologies. Section 1.4 outlines the history of related work and highlights the content of each chapter of this book.

scholarly journals A Cancelable Iris- and Steganography-Based User Authentication System for the Internet of Things

Sensors ◽  
2019 ◽  
Vol 19 (13) ◽  
pp. 2985 ◽  
Author(s):  
Wencheng Yang ◽  
Song Wang ◽  
Jiankun Hu ◽  
Ahmed Ibrahim ◽  
Guanglou Zheng ◽  
...  
Keyword(s):  
Internet Of Things ◽  
User Authentication ◽  
System Security ◽  
Random Projection ◽  
Biometric Data ◽  
Iot Security ◽  
Biometric Systems ◽  
Authentication System ◽  
Iot Devices ◽  
The Internet Of Things

Remote user authentication for Internet of Things (IoT) devices is critical to IoT security, as it helps prevent unauthorized access to IoT networks. Biometrics is an appealing authentication technique due to its advantages over traditional password-based authentication. However, the protection of biometric data itself is also important, as original biometric data cannot be replaced or reissued if compromised. In this paper, we propose a cancelable iris- and steganography-based user authentication system to provide user authentication and secure the original iris data. Most of the existing cancelable iris biometric systems need a user-specific key to guide feature transformation, e.g., permutation or random projection, which is also known as key-dependent transformation. One issue associated with key-dependent transformations is that if the user-specific key is compromised, some useful information can be leaked and exploited by adversaries to restore the original iris feature data. To mitigate this risk, the proposed scheme enhances system security by integrating an effective information-hiding technique—steganography. By concealing the user-specific key, the threat of key exposure-related attacks, e.g., attacks via record multiplicity, can be defused, thus heightening the overall system security and complementing the protection offered by cancelable biometric techniques.

scholarly journals Perbandingan Ekstraksi Fitur dan Proses Matching pada Autentikasi Sidik Jari Manusia

2020 ◽  
Vol 8 (1) ◽  
pp. 95
Author(s):  
ANGGUNMEKA LUHUR PRASASTI ◽  
BUDHI IRAWAN ◽  
SETIO EKA FAJRI ◽  
ANANDA RENDIKA ◽  
SUGONDO HADIYOSO
Keyword(s):  
Classification System ◽  
System Performance ◽  
Cross Correlation ◽  
Index Finger ◽  
Phase Correlation ◽  
Normalized Cross Correlation ◽  
Finger Vein ◽  
Maximum Curvature ◽  
Biometric Systems ◽  
Finger Recognition

ABSTRAK Sidik jari merupakan biometrik yang sering digunakan dalam teknologi autentikasi. Terdapat banyak metode yang bisa digunakan untuk membuat sistem klasifikasi sidik jari. Maximum Curvature Points (MCP) umumnya digunakan untuk ekstraksi citra pembuluh darah jari yang juga digunakan sebagai autentikasi. Pada penelitian ini akan diuji performansi dari metode MCP jika dibandingkan dengan metode yang umum digunakan pada proses pengenalan sidik jari, yaitu Hit and Miss Transform (HMT). Perbedaan domain, yaitu spasial pada Normalized Cross Correlation (NCC) dan frekuensi pada Phase Correlation (PC) dalam proses matching ternyata juga mempengaruhi performansi sistem. Hasilnya menunjukkan bahwa penggunakaan metode MHTNCC memiliki tingkat akurasi yang lebih baik dalam pengenalan sidik jari yaitu 92% untuk pengenalan ibu jari dan 98% untuk pengenalan jari telunjuk, dibandingkan dengan menggunakan metode MCP-PC yang hanya memiliki tingkat akurasi sebesar 88% untuk pengenalan ibu jari dan 92% untuk pengenalan jari telunjuk. Kata kunci: sidik jari, MCP, HMT, phase correlation, normalized cross correlation ABSTRACT Fingerprint is one of the biometric systems that are often used in an authentication technology. There are many methods that can be used to develop fingerprint’s classification system. Maximum Curvature Points (MCP) are generally used for finger vein image extraction which is also used as authentication. MCP performance will be compared to common method in finger print recognition, Hit and Miss Transform (HMT). Using different domains, spatial in Normalized Cross Correlation (NCC) and frequency in Phase Correlation (PC) affect the system performance. The results show that the application of HMT-NCC more accurate in terms of finger print’s recognition, 92% in accuracy for thumb recognition and 98% accuracy for index finger recognition, while MCP-PC is only reach 88% in accuracy for thumb recognition and 92% accuracy for index finger recognition. Keywords: fingerprint, MCP, HMT, phase correlation, normalized cross correlation

scholarly journals Incorporating Metadata in Multibiometric Score-Level Fusion: an Optimized Architecture

2019 ◽  
Vol 9 (1) ◽  
pp. 5290-5305
Keyword(s):  
Skin Color ◽  
Affective Computing ◽  
Biometric Data ◽  
Score Level Fusion ◽  
New Concepts ◽  
Biometric Systems ◽  
The Face ◽  
Ancillary Information ◽  
Biometric Information ◽  
Level Fusion

This manuscript presents a review on multibiometrics using ancillary information, in addition to the main biometric data. The proposed method involves taking non-biometric information into account in the biometric recognition process to improve system performance. This ancillary information can come from the user (the skin color), the sensor (the camera flash, etc.) or the operating environment (the ambient noise). Moreover, the paper presents an extension of the adapted sequential fusion framework through a complete description of the method used for the score-level fusion architecture presented at the IEEE BioSmart 2019 Proceedings. An optimized score-level fusion architecture is proposed. An introduction of new concepts (namely “biochemical features” and “multi origin biometrics”) is also made. The first part of the paper highlights the various biometric systems developed up to now, their architecture and characteristics. Then, the manuscript discussed about multibiometrics through its advantages, its diversity and the different levels of fusion. An attention was paid to the score-level fusion before addressing the consideration of ancillary information (or metadata) in multibiometrics. Dealing with the affective computing, the influence of emotion on the performance of biometric systems is explored. Finally, a typology of biometric adaptation is discussed. As an application, the proposed methodology will implement a multibiometric system using the face, contactless fingerprint and skin color. A single sensor will be used (a camera) with two shots while the skin color will be extracted automatically from the facial image.

scholarly journals Ochrona danych osobowych studentów w dobie rozwoju technologii biometrycznych wyzwaniem dla polskich uczelni

2020 ◽  
Vol 25 (4) ◽  
pp. 85-95
Author(s):  
Mateusz Kupiec ◽  
Keyword(s):  
European Union ◽  
Personal Data ◽  
Special Care ◽  
The European Union ◽  
Security Measures ◽  
Biometric Data ◽  
Biometric Systems ◽  
Legal Grounds

Biometric technologies have been gaining popularity lately. An increasing number of enterprises and public entities worldwide are using them for security measures. Many universities in the European Union have also begun to recognise the benefits of implementing biometric systems in their organisations, and it is just a matter of time before universities in Poland join them as well. However, biometric data used by such systems are especially sensitive as they may reveal intimate information about data subjects. As such, they are counted among special categories of personal data, the processing of which is in principle prohibited by art. 9 (1) GPDR. Furthermore, the processing of students’ personal data demands special care from universities as they are vulnerable data subjects. Students are namely subordinate to university authorities, which significantly limits their scope of autonomy. Therefore, the use of biometric technologies poses a challenge for universities in Poland. The following article aims to present the main reasons why students are vulnerable data subjects and which legal grounds provided by GDPR are most suitable for processing their biometric data by universities.

scholarly journals Integration of Biometrics and Steganography: A Comprehensive Review

Technologies ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 34 ◽  
Author(s):  
Ian McAteer ◽  
Ahmed Ibrahim ◽  
Guanglou Zheng ◽  
Wencheng Yang ◽  
Craig Valli
Keyword(s):  
Future Research ◽  
Security Model ◽  
Biometric Data ◽  
Current Dependence ◽  
The Public ◽  
Industry Standards ◽  
Legal Implications ◽  
Biometric Systems ◽  
The Subject ◽  
Secure Transmission

The use of an individual’s biometric characteristics to advance authentication and verification technology beyond the current dependence on passwords has been the subject of extensive research for some time. Since such physical characteristics cannot be hidden from the public eye, the security of digitised biometric data becomes paramount to avoid the risk of substitution or replay attacks. Biometric systems have readily embraced cryptography to encrypt the data extracted from the scanning of anatomical features. Significant amounts of research have also gone into the integration of biometrics with steganography to add a layer to the defence-in-depth security model, and this has the potential to augment both access control parameters and the secure transmission of sensitive biometric data. However, despite these efforts, the amalgamation of biometric and steganographic methods has failed to transition from the research lab into real-world applications. In light of this review of both academic and industry literature, we suggest that future research should focus on identifying an acceptable level steganographic embedding for biometric applications, securing exchange of steganography keys, identifying and address legal implications, and developing industry standards.

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