This thesis studies the requirements and processes involved in building an authentication system using the fingerprint biometric, where the fingerprint template is protected during storage and during comparison. The principles developed in this thesis can be easily extended to authentication systems using other biometric modalities. Most existing biometric authentication systems store their template securely using an encryption function. However, in order to perform matching, the enrolled template must be decrypted. It is at this point that the authentication system is most vulnerable as the entire enrolled template is exposed. A biometric is irreplaceable if compromised and can also reveal sensitive information about an individual. If biometric systems are taken up widely, the template could also be used as an individual's digital identifier. Compromise in that case, violates an individual's right to privacy as their transactions in all systems where they used that compromised biometric can be tracked. Therefore securing a biometric template during comparison as well as storage in an authentication system is imperative. Eight different fingerprint template representation techniques, where templates were treated as a set of elements derived from the locations and orientations of fingerprint minutiae, were studied. Four main steps to build any biometric based authentication system were identified and each of the eight fingerprint template representations was inducted through the four steps. Two distinct Error Tolerant Cryptographic Constructs based on the set difference metric, were studied for their ability to securely store and compare each of the template types in an authentication system. The first construct was found to be unsuitable for a fundamental reason that would apply to all the template types considered in the research. The second construct did not have the limitation of the first and three algorithms to build authentication systems using the second construct were proposed. It was determined that minutiae-based templates had significant intra sample variation as a result of which a very relaxed matching threshold had to be set in the authentication system. The relaxed threshold caused the authentication systems built using the first two algorithms to reveal enough information about the stored templates to render them insecure. It was found that in cases of such large intra-sample variation, a commonality based match decision was more appropriate. One solution to building a secure authentication system using minutiae-based templates was demonstrated by the third algorithm which used a two stage matching process involving the second cryptographic construct and a commonality based similarity measure in the two stages respectively. This implementation was successful in securing the fingerprint template during comparison as well as storage, with minimal reduction in accuracy when compared to the matching performance without the cryptographic construct. Another solution is to use an efficient commonality based error tolerant cryptographic construct. This thesis lists the desirable characteristics of such a construct as existence of any is unknown to date. This thesis concludes by presenting good guidelines to evaluate the suitability of different cryptographic constructs to protect biometric templates of other modalities in an authentication system.

Future-generation wireless and mobile networks are expected to support a panoply of multimedia services, ranging from voice to video data. There is also a de facto "anytime anywhere" mentality that reliable communications should be ubiquitously guaranteed, irrespective of temporal or geographical constraints. However, the implicit catch is that these specifications should be achieved with only minimal infrastructure expansion or cost increases. In this thesis, various signal processing methodologies conducive to attaining these goals are presented. First, a system model that takes into account the time-varying nature of the mobile environment is developed. To this end, a mathematically tractable basis-expansion model (BEM) of the communication channel, augmented with multiple-state characterization, is proposed. In the context of the developed system model, strategies for enhancing the quality of service (QoS), while maintaining resource efficiency, are then studied. Specifically, dynamic channel tracking, adaptive modulation and coding, interpolation and random sampling, and spatiotemporal processing are examined as enabling solutions. Next, the question of how to appropriately aggregate these disparate methods is recast as a nonlinear constrained optimization problem. This enables the construction of a flexible framework that can accommodate a wide range of applications, to deliver practical network designs. In particular, the developed methods are well-suited for multi-user communication systems, implemented using spread-spectrum and multi-carrier solutions, such as code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). Moreover, privacy and security requirements are increasingly becoming essential aspects of the QoS paradigm in communications. Combined with the advent of novel security technologies, such as biometrics, the conventional communication infrastructure is expected to undergo fundamental modifications to support these new system components and modalities. Therefore, within the same framework for maximizing resource efficiency, several unique signal processing applications in network security using biometrics are also investigated in this thesis. It is shown that a resource allocation approach is equally appropriate, and productive, in delivering efficient and practical key distribution and biometric encryption solutions for secure communications.

Future-generation wireless and mobile networks are expected to support a panoply of multimedia services, ranging from voice to video data. There is also a de facto "anytime anywhere" mentality that reliable communications should be ubiquitously guaranteed, irrespective of temporal or geographical constraints. However, the implicit catch is that these specifications should be achieved with only minimal infrastructure expansion or cost increases. In this thesis, various signal processing methodologies conducive to attaining these goals are presented. First, a system model that takes into account the time-varying nature of the mobile environment is developed. To this end, a mathematically tractable basis-expansion model (BEM) of the communication channel, augmented with multiple-state characterization, is proposed. In the context of the developed system model, strategies for enhancing the quality of service (QoS), while maintaining resource efficiency, are then studied. Specifically, dynamic channel tracking, adaptive modulation and coding, interpolation and random sampling, and spatiotemporal processing are examined as enabling solutions. Next, the question of how to appropriately aggregate these disparate methods is recast as a nonlinear constrained optimization problem. This enables the construction of a flexible framework that can accommodate a wide range of applications, to deliver practical network designs. In particular, the developed methods are well-suited for multi-user communication systems, implemented using spread-spectrum and multi-carrier solutions, such as code division multiple access (CDMA) and orthogonal frequency division multiplexing (OFDM). Moreover, privacy and security requirements are increasingly becoming essential aspects of the QoS paradigm in communications. Combined with the advent of novel security technologies, such as biometrics, the conventional communication infrastructure is expected to undergo fundamental modifications to support these new system components and modalities. Therefore, within the same framework for maximizing resource efficiency, several unique signal processing applications in network security using biometrics are also investigated in this thesis. It is shown that a resource allocation approach is equally appropriate, and productive, in delivering efficient and practical key distribution and biometric encryption solutions for secure communications.

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

Personal identity refers to a set of attributes (e.g., name, social insurance number, etc.) that are associated with a person. Identity management is the process of creating, maintaining and destroying identities of individuals in a population. Biometric technologies are technologies developed to use statistical analysis of an individual’s biological or behavioral traits to determine his identity. Biometrics based authentication systems offer a reliable solution for identity management, because of their uniqueness, relative stability over time and security (among other reasons). Public acceptance of biometric systems will depend on their ability to ensure robustness, accuracy and security. Although robustness and accuracy of such systems are rapidly improving, there still remain some issues of security and balancing it with privacy. While the uniqueness of biometric traits offers a convenient and reliable means of identification, it also poses the risk of unauthorized cross-referencing among databases using the same biometric trait. There is also a high risk in case of a biometric database being compromised, since it’s not possible to revoke the biometric trait and re-issue a new one as is the case with passwords and smart keys. This unique attribute of biometric based authentication system poses a challenge that might slow down public acceptance and the use of biometrics for authentication purposes in large scale applications. In this research we investigate the vulnerabilities of biometric systems focusing on template security in iris-based biometric recognition systems. The iris has been well studied for authentication purposes and has been proven accurate in large scale applications in several airports and border crossings around the world. The most widely accepted iris recognition systems are based on Daugman’s model that creates a binary iris template. In this research we develop different systems using watermarking, bio-cryptography as well as feature transformation to achieve revocability and security of binary templates in iris based biometric authentication systems, while maintaining the performance that enables widespread application of these systems. All algorithms developed in this research are applicable on already existing biometric authentication systems and do not require redesign of these existing, well established iris-based authentication systems that use binary templates.

The research conducted under this study offers an understanding of the reasons why information technology (IT) and/or information assurance (IA) managers choose to recommend or not to recommend particular technologies, specifically biometric security, to their organizations. A review of the relevant literature provided the foundation to develop a set of research questions and factors for this research effort. The research questions became the basis of the study’s stated hypotheses for examining managers’ perceptions of the security effectiveness, need, reliability, and cost-effectiveness of biometrics. The research indicates that positive perceptions of security effectiveness, need, reliability, and cost-effectiveness correlate with IT/IA managers’ willingness to recommend biometric security technologies. The implications of this study are that executives and managers can make informed decisions about the recommendation and adoption process relevant to biometric security technologies through an understanding of how perceptions of biometric technology affect the decision to recommend this type of technology. The study’s results may also help biometric product developers, vendors, and marketers understand the important perceptions of biometric security technologies within their customer base of IT/IA managers.

Indiana University-Purdue University Indianapolis (IUPUI) / A large portion of system breaches are caused by authentication failure either during the system login process or even in the post-authentication session, which is further related to the limitations associated with existing authentication approaches. Current authentication methods, whether proxy based or biometrics based, are hardly user-centric; and they either put burdens on users or endanger users' (biometric) security and privacy. In this research, we propose a biometrics based user-centric authentication approach. The main idea is to introduce a reference subject (RS) (for each system), securely fuse the user's biometrics with the RS, generate a BioCapsule (BC) (from the fused biometrics), and employ BCs for authentication. Such an approach is user-friendly, identity-bearing yet privacy-preserving, resilient, and revocable once a BC is compromised. It also supports "one-click sign on" across multiple systems by fusing the user's biometrics with a distinct RS on each system. Moreover, active and non-intrusive authentication can be automatically performed during the user's post-authentication on-line session. In this research, we also formally prove that the proposed secure fusion based BC approach is secure against various attacks and compare the new approach with existing biometrics based approaches. Extensive experiments show that the performance (i.e., authentication accuracy) of the new BC approach is comparable to existing typical biometric authentication approaches, and the new BC approach also possesses other desirable features such as diversity and revocability.