Thesis (M.S.)--West Virginia University, 2007. / Title from document title page. Document formatted into pages; contains viii, 95 p. : ill. (some col.). Includes abstract. Includes bibliographical references (p. 92-95).

Designing a completely secure and trusted system is a challenge that still needs to be addressed. Currently, there is no online system that is: (i) easy to use, (ii) easy to deploy, (iii) inexpensive, and (iv) completely secure and trusted. The proposed authentication techniques aim to enhance security and trust for video applications in the untrustworthy online environments. We propose a transparent multimodal biometric authentication (TMBA) for video conferencing applications. The user is identified based on his/her physiological and behavioral biometrics. The technique is based on a ‘Steps-Free’ method, where the user does not have to perform any specific steps during authentication. The system will authenticate the user in a transparent way. We propose authentication techniques as an additional security layer for various ‘user-to-user’ and ‘user-to-service’ systems. For ‘user-to-user’ video conferencing systems, we propose an authentication and trust establishment procedure to identify users during a video conference. This technique enables users that have never met before to verify the identity of each other, and aims at enhancing the user’s trust in each other. For ‘user-to-service’ video conferencing systems, we propose a transparent multimodal biometric authentication technique for video banking. The technique can be added to online transaction systems as an additional security layer to enhance the security of online transactions, and to resist against web attacks, malware, and Man-In-The-Browser (MITB) attacks. In order to have a video banking conference between a user and a bank employee, the user has to be logged in to an online banking session. This requires a knowledge-based authentication. Knowledge-based authentication includes a text-based password, the ‘Challenge Questions’ method, and graphical passwords. We analyzed several graphical password schemes in terms of usability and security factors. A graphical password scheme can be an additional security layer add-on to the proposed multimodal biometric video banking system. The combined techniques provide a multimodal biometric multi-factor continuous authentication system.

M.Sc. / A Smart Card looks like a normal plastic card that we use every day, but its capabilities and advantages are huge. Inside the card there is a small microprocessor capable of doing operations on data. With memory available on the card, data can be stored in a safe and secure location. This card can be used for various applications and is a big improvement on all of its predecessors. These applications can be anything from SIM cards in a cell phone to credit cards and cards used for access control. The Smart Card offers us better security and offline identification because of its own embedded microprocessor. The combination of Smart Cards with biometrics for security reasons will be a logical step and the ideal way to identify the person as the true owner of the card. This dissertation will investigate the use of contact Smart Cards in the University environment, more specifically as a University student card. The Smart Card will be combined with a fingerprint to enforce better security. The main purpose is to use the Smart Card and the biometric property for access control at various places on campus.

M.Ing. (Electrical And Electronic Engineering) / Iris recognition systems have attracted much attention for their uniqueness, stability and reliability. This recognition system is composed of four main modules, namely, iris acquisition, iris segmentation, feature extraction and encoding and - nally iris matching. However, performance of this system is a ected by poor image quality. In this research, a novel iris image quality assessment method based on character component is presented. This method is composed of two steps, individual assessment of character quality parameters and fusion of estimated quality parameters using Principal Component Analysis (PCA). The de ned quality parameters considered in this research are entropy, sharpness, occlusion, dilation, area ratio, contrast and blur. The designed technique was tested on three databases: Chinese Academy of Science Institute of Automation (CASIA), University of Beira Interior (UBIRIS) and Internal Collection (IC). Individual assessment of quality parameters has shown that dilation, sharpness and blur have more in uence on the quality score than the other parameters. The images were classi ed into two categories (good and bad) by human visual inspection. The e ect of the individual parameters on each database is illustrated, with CASIA exhibiting higher quality scores than the UBIRIS and IC databases. Support Vector Machine (SVM) and Linear Discriminant Analysis (LDA) were used to evaluate the performance of the proposed quality assessment algorithm. A k-fold cross validation technique was employed to the classi ers to obtain unbiased results. Two performance measures were used to rate the proposed algorithm, namely, Correct Rate (CR) and Area Under the Curve (AUC). Both performance measures showed that SVM classi er outperforms LDA in correctly classifying the quality of the images in all three databases. The experimental results demonstrated that the proposed algorithm is capable of detecting poor quality images as it yields an e ciency of over 84% and 90% in CR and AUC respectively. The use of character component to assess quality has been found to be su cient, though there is a need to develop a better technique for standardization of quality. The results found using a SVM classi er a rms the proposed algorithm is well-suited for quality assessment.

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Yes / Biometric authentication is the science and engineering of assessing and evaluating bioinformatics from the human body in order to increase system security by providing reliable and accurate behaviors and classifiers for personal identification and authentication. Its solutions are widely used in industries, governments, and the military. This paper reviews the multimodal biometric systems that integrated both faces and fingerprints as well as shows which one has the best accuracy and hardware complexity with the methods and databases. Several methods have been used in multimodal biometric systems such as KNN (K-Nearest Neighbor), CNN (Convolutional Neural Network), PCA (Principal Component Analysis), and so on. A multimodal biometric system for face and fingerprints that uses an FoM (Figure of Merit) to compare and show between the articles the best accuracy that have used multimodal biometric system face and fingerprints methods. The best performance has been found is 99.43% by using the cascade multimodal method. / Horizon-MSCA-RISE-2019-2023, Marie Sklodowska-Curie

Abstract INDIVIDUAL-TECHNOLOGY FIT: MATCHING INDIVIDUAL CHARACTERISTICS AND FEATURES OF BIOMETRIC INTERFACE TECHNOLOGIES WITH PERFORMANCE By ADRIANE B. RANDOLPH MAY 2007 Committee Chair: Dr. Melody Moore Jackson Major Department: Computer Information Systems The term biometric literally means “to measure the body”, and has recently been associated with physiological measures commonly used for personal verification and security applications. In this work, biometric describes physiological measures that may be used for non-muscularly controlled computer applications, such as brain-computer interfaces. Biometric interface technology is generally targeted for users with severe motor disabilities which may last long-term due to illness or injury or short-term due to temporary environmental conditions. Performance with a biometric interface can vary widely across users depending upon many factors ranging from health to experience. Unfortunately, there is no systematic method for pairing users with biometric interface technologies to achieve the best performance. The current methods to accommodate users through trial-and-error result in the loss of valuable time and resources as users sometimes have diminishing abilities or suffer from terminal illnesses. This dissertation presents a framework and methodology that links user characteristics and features of biometric interface technologies with performance, thus expediting the technology-fit process. The contributions include an outline of the underlying components of capturing and representing individual user characteristics and the impact on the performance of basic interaction tasks using a methodology called biometric user profiling. In addition, this work describes a methodology for objectively measuring an individual’s ability to control a specific biometric interface technology such as one based on measures of galvanic skin response or neural activity. Finally, this work incorporates these concepts into a new individual-technology fit framework for biometric interface technologies stemming from literature on task-technology fit. Key words: user profiles, biometric user profiling, biometric interfaces, fit, individual-technology fit, galvanic skin response, functional near-infrared, brain-computer interface

Indiana University-Purdue University Indianapolis (IUPUI) / Biometrics identi es/veri es a person using his/her physiological or behavioral characteristics. It is becoming an important ally for law enforcement and homeland security. Among all the biometric modalities, iris is tested to be the most accurate one. However, most existing methods are not designed for non-cooperative users and cannot work with o -angle or low quality iris images. In this thesis, we propose a robust multi-stage feature extraction and matching approach for non-cooperative iris recognition. We developed the SURF-like method to extract stable feature points, used Gabor Descriptor method for local feature description, and designed the multi- stage feature extraction and matching scheme to improve the recognition accuracy and speed. The related experimental results show that the proposed method is very promising. In addition, two template security enhanced schemes for the proposed non- cooperative iris recognition are introduced. The related experimental results show that these two schemes can e ectively realize cancelability of the enrolled biometric templates while at the same time achieving high accuracy.

M.Sc. / Determining the identity of a person has become vital in today’s world. Emphasis on security has become increasingly more common in the last few decades, not only in Information Technology, but across all industries. One of the main principles of security is that a system only be accessed by a legitimate user. According to the ISO 7498/2 document [1] (an international standard which defines an information security system architecture) there are 5 pillars of information security. These are Identification/Authentication, Confidentiality, Authorization, Integrity and Non Repudiation. The very first line of security in a system is identifying and authenticating a user. This ensures that the user is who he/she claims to be, and allows only authorized individuals to access your system. Technologies have been developed that can automatically recognize a person by his unique physical features. This technology, referred to as ‘biometrics’, allows us to quickly, securely and conveniently identify an individual. Biometrics solutions have already been deployed worldwide, and it is rapidly becoming an acceptable method of identification in the eye of the public. As useful and advanced as unimodal (single biometric sample) biometric technologies are, they have their limits. Some of them aren’t completely accurate; others aren’t as secure and can be easily bypassed. Recently it has been reported to the congress of the U.S.A [2] that about 2 percent of the population in their country do not have a clear enough fingerprint for biometric use, and therefore cannot use their fingerprints for enrollment or verification. This same report recommends using a biometric system with dual (multimodal) biometric inputs, especially for large scale systems, such as airports. In this dissertation we will investigate and compare multimodal biometric techniques, in order to determine how much of an advantage lies in using this technology, over its unimodal equivalent.

A dissertation submitted to the Faculty of Science, University of the Witwatersrand, Johannesburg, in fulfilment of requirements for the degree of Master of Science, School of Computer Science and Applied Mathematics. May 2017. / Biometric features have been widely implemented to be utilized for forensic and civil applications. Amongst many different kinds of biometric characteristics, the fingerprint is globally accepted and remains the mostly used biometric characteristic by commercial and industrial societies due to its easy acquisition, uniqueness, stability and reliability. There are currently various effective solutions available, however the fingerprint identification is still not considered a fully solved problem mainly due to accuracy and computational time requirements. Although many of the fingerprint recognition systems based on minutiae provide good accuracy, the systems with very large databases require fast and real time comparison of fingerprints, they often either fail to meet the high performance speed requirements or compromise the accuracy. For fingerprint matching that involves databases containing millions of fingerprints, real time identification can only be obtained through the implementation of optimal algorithms that may utilize the given hardware as robustly and efficiently as possible. There are currently no known distributed database and computing framework available that deal with real time solution for fingerprint recognition problem involving databases containing as many as sixty million fingerprints, the size which is close to the size of the South African population. This research proposal intends to serve two main purposes: 1) exploit and scale the best known minutiae matching algorithm for a minimum of sixty million fingerprints; and 2) design a framework for distributed database to deal with large fingerprint databases based on the results obtained in the former item. / GR2018