Biometrics and Network Security

This paper examines the techniques used in the two categories of biometric techniques (physiological and behavioral) and considers some of the applications for biometric technologies. Common physiological biometrics include finger characteristics (fingertip [fingerprint], thumb, finger length or pattern), palm (print or topography), hand geometry, wrist vein, face, and eye (retina or iris). Behavioral biometrics include voiceprints, keystroke dynamics, and handwritten signatures

Body language, security and e-commerce

Security is becoming an increasingly more important concern both at the desktop level and at the network level. This article discusses several approaches to authenticating individuals through the use of biometric devices. While libraries might not implement such devices, they may appear in the near future of desktop computing, particularly for access to institutional computers or for access to sensitive information. Other approaches to computer security focus on protecting the contents of electronic transmissions and verification of individual users. After a brief overview of encryption technologies, the article examines public-key cryptography which is getting a lot of attention in the business world in what is called public key infrastructure. It also examines other efforts, such as IBM’s Cryptolope, the Secure Sockets Layer of Web browsers, and Digital Certificates and Signatures. Secure electronic transmissions are an important condition for conducting business on the Net. These business transactions are not limited to purchase orders, invoices, and contracts. This could become an important tool for information vendors and publishers to control access to the electronic resources they license. As license negotiators and contract administrators, librarians need to be aware of what is happening in these new technologies and the impact that will have on their operations

Age Detection Through Keystroke Dynamics From User Authentication Failures

In this paper an incident response approach is proposed for handling detections of authentication failures in systems that employ dynamic biometric authentication and more specifically keystroke user recognition. The main component of the approach is a multi layer perceptron focusing on the age classification of a user. Empirical findings show that the classifier can detect the age of the subject with a probability that is far from the uniform random distribution, making the proposed method suitable for providing supporting yet circumstantial evidence during e-discovery

Identification and Security Implications of Biometrics

The usage of biometrics has become more frequent over the past couple of decades, notably due to technological advancements. Evolving technology in the field of biometrics has also led to increased accuracy of associated software, which have provided the opportunity to use a multitude of different human characteristics for identification and/or verification purposes. The current study assessed the usage of biometrics in casinos, hospitals, and law enforcement agencies using a survey methodology. Results indicated that privacy concerns related to the use of biometrics may not be as prevalent as indicated in the literature. Additionally, results indicated that the utilization of biometrics has led to increased accuracy in identification and verification processes, led to enhanced security, and would be highly recommended to other institutions. Information obtained from the literature notes the racial bias in facial recognition technologies due to algorithmic development based solely upon features of Caucasian individuals. Efforts need to be made to create facial recognition algorithms that are more racially and ethnically diverse

Establishing the digital chain of evidence in biometric systems

Traditionally, a chain of evidence or chain of custody refers to the chronological documentation, or paper trail, showing the seizure, custody, control, transfer, analysis, and disposition of evidence, physical or electronic. Whether in the criminal justice system, military applications, or natural disasters, ensuring the accuracy and integrity of such chains is of paramount importance. Intentional or unintentional alteration, tampering, or fabrication of digital evidence can lead to undesirable effects. We find despite the consequences at stake, historically, no unique protocol or standardized procedure exists for establishing such chains. Current practices rely on traditional paper trails and handwritten signatures as the foundation of chains of evidence.;Copying, fabricating or deleting electronic data is easier than ever and establishing equivalent digital chains of evidence has become both necessary and desirable. We propose to consider a chain of digital evidence as a multi-component validation problem. It ensures the security of access control, confidentiality, integrity, and non-repudiation of origin. Our framework, includes techniques from cryptography, keystroke analysis, digital watermarking, and hardware source identification. The work offers contributions to many of the fields used in the formation of the framework. Related to biometric watermarking, we provide a means for watermarking iris images without significantly impacting biometric performance. Specific to hardware fingerprinting, we establish the ability to verify the source of an image captured by biometric sensing devices such as fingerprint sensors and iris cameras. Related to keystroke dynamics, we establish that user stimulus familiarity is a driver of classification performance. Finally, example applications of the framework are demonstrated with data collected in crime scene investigations, people screening activities at port of entries, naval maritime interdiction operations, and mass fatality incident disaster responses

Continuous User Authentication Using Multi-Modal Biometrics

It is commonly acknowledged that mobile devices now form an integral part of an individual’s everyday life. The modern mobile handheld devices are capable to provide a wide range of services and applications over multiple networks. With the increasing capability and accessibility, they introduce additional demands in term of security. This thesis explores the need for authentication on mobile devices and proposes a novel mechanism to improve the current techniques. The research begins with an intensive review of mobile technologies and the current security challenges that mobile devices experience to illustrate the imperative of authentication on mobile devices. The research then highlights the existing authentication mechanism and a wide range of weakness. To this end, biometric approaches are identified as an appropriate solution an opportunity for security to be maintained beyond point-of-entry. Indeed, by utilising behaviour biometric techniques, the authentication mechanism can be performed in a continuous and transparent fashion. This research investigated three behavioural biometric techniques based on SMS texting activities and messages, looking to apply these techniques as a multi-modal biometric authentication method for mobile devices. The results showed that linguistic profiling; keystroke dynamics and behaviour profiling can be used to discriminate users with overall Equal Error Rates (EER) 12.8%, 20.8% and 9.2% respectively. By using a combination of biometrics, the results showed clearly that the classification performance is better than using single biometric technique achieving EER 3.3%. Based on these findings, a novel architecture of multi-modal biometric authentication on mobile devices is proposed. The framework is able to provide a robust, continuous and transparent authentication in standalone and server-client modes regardless of mobile hardware configuration. The framework is able to continuously maintain the security status of the devices. With a high level of security status, users are permitted to access sensitive services and data. On the other hand, with the low level of security, users are required to re-authenticate before accessing sensitive service or data

A computational academic integrity framework

L'abast creixent i la naturalesa canviant dels programes acadèmics constitueixen un repte per a la integritat dels protocols tradicionals de proves i exàmens. L'objectiu d¿aquesta tesi és introduir una alternativa als enfocaments tradicionals d'integritat acadèmica, per a cobrir la bretxa del buit de l'anonimat i donar la possibilitat als instructors i administradors acadèmics de fer servir nous mitjans que permetin mantenir la integritat acadèmica i promoguin la responsabilitat, accessibilitat i eficiència, a més de preservar la privadesa i minimitzin la interrupció en el procés d'aprenentatge. Aquest treball té com a objectiu començar un canvi de paradigma en les pràctiques d'integritat acadèmica. La recerca en l'àrea de la identitat de l'estudiant i la garantia de l'autoria són importants perquè la concessió de crèdits d'estudi a entitats no verificades és perjudicial per a la credibilitat institucional i la seguretat pública. Aquesta tesi es basa en la noció que la identitat de l'alumne es compon de dues capes diferents, física i de comportament, en les quals tant els criteris d'identitat com els d'autoria han de ser confirmats per a mantenir un nivell raonable d'integritat acadèmica. Per a això, aquesta tesi s'organitza en tres seccions, cadascuna de les quals aborda el problema des d'una de les perspectives següents: (a) teòrica, (b) empírica i (c) pragmàtica.El creciente alcance y la naturaleza cambiante de los programas académicos constituyen un reto para la integridad de los protocolos tradicionales de pruebas y exámenes. El objetivo de esta tesis es introducir una alternativa a los enfoques tradicionales de integridad académica, para cubrir la brecha del vacío anonimato y dar la posibilidad a los instructores y administradores académicos de usar nuevos medios que permitan mantener la integridad académica y promuevan la responsabilidad, accesibilidad y eficiencia, además de preservar la privacidad y minimizar la interrupción en el proceso de aprendizaje. Este trabajo tiene como objetivo iniciar un cambio de paradigma en las prácticas de integridad académica. La investigación en el área de la identidad del estudiante y la garantía de la autoría son importantes porque la concesión de créditos de estudio a entidades no verificadas es perjudicial para la credibilidad institucional y la seguridad pública. Esta tesis se basa en la noción de que la identidad del alumno se compone de dos capas distintas, física y de comportamiento, en las que tanto los criterios de identidad como los de autoría deben ser confirmados para mantener un nivel razonable de integridad académica. Para ello, esta tesis se organiza en tres secciones, cada una de las cuales aborda el problema desde una de las siguientes perspectivas: (a) teórica, (b) empírica y (c) pragmática.The growing scope and changing nature of academic programmes provide a challenge to the integrity of traditional testing and examination protocols. The aim of this thesis is to introduce an alternative to the traditional approaches to academic integrity, bridging the anonymity gap and empowering instructors and academic administrators with new ways of maintaining academic integrity that preserve privacy, minimize disruption to the learning process, and promote accountability, accessibility and efficiency. This work aims to initiate a paradigm shift in academic integrity practices. Research in the area of learner identity and authorship assurance is important because the award of course credits to unverified entities is detrimental to institutional credibility and public safety. This thesis builds upon the notion of learner identity consisting of two distinct layers (a physical layer and a behavioural layer), where the criteria of identity and authorship must both be confirmed to maintain a reasonable level of academic integrity. To pursue this goal in organized fashion, this thesis has the following three sections: (a) theoretical, (b) empirical, and (c) pragmatic

Adversarial Activity Detection and Prediction Using Behavioral Biometrics

Behavioral biometrics can be used in different security applications like authentication, identification, etc. One of the trending applications is predicting future activities of people and guessing whether they will engage in malicious activities in the future. In this research, we study the possibility of predicting future activities and propose novel methods for near-future activity prediction. First, we study gait signals captured using smartphone accelerometer sensor and build a model to predict a future gait signal. Activity recognition using body movements captured from mobile phone sensors has been a major point of interest in recent research. Data that is being continuously read from mobile sensors can be used to recognize user activity. We propose a model for predicting human body movements based on the previous activity that has been read from sensors and continuously updating our prediction as new data becomes available. Our results show that our model can predict the future movement signal with a high accuracy that can contribute to several applications in the area. Second, we study keystroke acoustics and build a model for predicting future activities of the users by recording their keystrokes audio. Using keystroke acoustics to predict typed text has significant advantages, such as being recorded covertly from a distance and requiring no physical access to the computer system. Recently, some studies have been done on keystroke acoustics, however, to the best of our knowledge none have used them to predict adversarial activities. On a dataset of two million keystrokes consisting of seven adversarial and one benign activity, we use a signal processing approach to extract keystrokes from the audio and a clustering method to recover the typed letters followed by a text recovery module to regenerate the typed words. Furthermore, we use a neural network model to classify the benign and adversarial activities and achieve significant results: (1) we extract individual keystroke sounds from the raw audio with 91% accuracy and recover words from audio recordings in a noisy environment with 71% average top-10 accuracy. (2) We classify adversarial activities with 93% to 98% average accuracy under different operating scenarios. Third, we study the correlation between the personality traits of users with their keystroke and mouse dynamics. Even with the availability of multiple interfaces, such as voice, touch, etc., keyboard and mouse remain the primary interfaces to a computer. Any insights on the relation between keyboard and mouse dynamics with the personality type of the users can provide foundations for various applications, such as advertisement, social media, etc. We use a dataset of keystroke and mouse dynamics collected from 104 users together with their responses to two personality tests to analyze how their interaction with the computer relates to their personality. Our findings show that there are considerable trends and patterns in keystroke and mouse dynamics that are correlated with each personality type

Future Security Approaches and Biometrics

Threats to information security are proliferating rapidly, placing demanding requirements on protecting tangible and intangible business and individual assets. Biometrics can improve security by replacing or complementing traditional security technologies. This tutorial discusses the strengths and weaknesses of biometrics and traditional security approaches, current and future applications of biometrics, performance evaluation measures of biometric systems, and privacy issues surrounding the new technology

Securing Inter-Organizational Workflows in Highly Dynamic Environments through Biometric Authentication

High flexibility demands of business processes in an inter-organizational context potentially conflict with existing security needs, mainly implied by regulative and legal requirements. In order to comply with these it has to be ensured that access to information within the workflow is restricted to authorized participants. Furthermore, the system might be required to prove this retrospectively. In highly flexible environments, particularly when documents leave the owner’s security domain, the scope of trust must be expendable throughout the workflow. Usage control provides practical concepts. However, user authentication remains a major vulnerability. In order to ensure effective access control the possibility of process-wide enforcement of strong authentication is needed. Inherently, strong user authentication can be realized applying biometrics, though practical reasons still slow the broad application of biometric authentication methods in common workflow scenarios. This work proposes the combination of usage control and typing biometrics to secure interorganizational workflows in highly dynamic environments. On the one hand, usage control provides high flexibility for document-centric workflows but relies on the enforcement of strong authentication. On the other hand, authentication based on typing is flexible in both deployment and application. Furthermore, the inherent privacy problem of biometrics is significantly weakened by the proposed approach