Physical Sciences and Mathematics Commons^™

Legislative Recommendations On Biometric Security And Privacy Jurisprudence, Joshua M. Morrow

All Student Scholarship

This project focuses on the prevalence of biometrics today, their various applications, and the biometric laws and legislations in place in the United States (U.S.) and Maine. Due to various threats and vulnerabilities imposing risk on collecting and using peoples’ biometric data, sufficient cyber protections related to citizens’ privacy rights, ethical control, and security of personally identifiable information (PII) must become necessary components of contemporary biometric laws and legislation. Without such explicit cyber protections, citizens participate in and comply with various technical domains and entities, such as private companies and governmental agencies, with minimal awareness or comprehension that their sensitive …

Implementing Unmanned Aerial Vehicles To Collect Human Gait Data At Distance And Altitude For Identification And Re-Identification, Donn E. Bartram

Graduate Theses, Dissertations, and Problem Reports

Gait patterns are a class of biometric information pertaining to the way a person moves and poses. Gait information is unique to each person and can be used to identify and reidentify people. Historically, this task has been achieved through the use of multiple ground-based imaging sensors. However, as Unmanned Aerial Vehicles (UAVs) advance, they present the opportunity to evolve the process of persons identification and re-identification. Collecting human gait data using UAVs at distances ranging from 20m to 500m and altitudes ranging from 0m to 120m is a challenging task. The current biometric data collection methods, primarily designed for …

Fedbiometric: Image Features Based Biometric Presentation Attack Detection Using Hybrid Cnns-Svm In Federated Learning, S M Sarwar

Theses and Dissertations

In the past few years, biometric identification systems have become popular for personal, national, and global security. In addition to other biometric modalities, facial and fingerprint recognition have gained popularity due to their uniqueness, stability, convenience, and cost-effectiveness compared to other biometric modalities. However, the evolution of fake biometrics, such as printed materials, 2D or 3D faces, makeup, and cosmetics, has brought new challenges. As a result of these modifications, several facial and fingerprint Presentation Attack Detection methods have been proposed to distinguish between live and spoof faces or fingerprints. Federated learning can play a significant role in this problem …

Sequence Checking And Deduplication For Existing Fingerprint Databases, Tahsin Islam Sakif

Graduate Theses, Dissertations, and Problem Reports

Biometric technology is a rapidly evolving field with applications that range from access to devices to border crossing and entry/exit processes. Large-scale applications to collect biometric data, such as border crossings result in multimodal biometric databases containing thousands of identities. However, due to human operator error, these databases often contain many instances of image labeling and classification; this is due to the lack of training and throughput pressure that comes with human error. Multiple entries from the same individual may be assigned to a different identity. Rolled fingerprints may be labeled as flat images, a face image entered into a …

Keystroke Dynamics And User Identification, Atharva Sharma

Master's Projects

We consider the potential of keystroke dynamics for user identification and authentication. We work with a fixed-text dataset, and focus on clustering users based on the difficulty of distinguishing their typing characteristics. After obtaining a confusion matrix, we cluster users into different levels of classification difficulty based on their typing patterns. Our goal is to create meaningful clusters that enable us to apply appropriate authentication methods to specific user clusters, resulting in an optimized balance between security and efficiency. We use a novel feature engineering method that generates image-like features from keystrokes and employ multiclass Convolutional Neural Networks (CNNs) to …

An Analysis On Adversarial Machine Learning: Methods And Applications, Ali Dabouei

Graduate Theses, Dissertations, and Problem Reports

Deep learning has witnessed astonishing advancement in the last decade and revolutionized many fields ranging from computer vision to natural language processing. A prominent field of research that enabled such achievements is adversarial learning, investigating the behavior and functionality of a learning model in presence of an adversary. Adversarial learning consists of two major trends. The first trend analyzes the susceptibility of machine learning models to manipulation in the decision-making process and aims to improve the robustness to such manipulations. The second trend exploits adversarial games between components of the model to enhance the learning process. This dissertation aims to …

On The Study Of Age-Related Physiological Decline In C. Elegans, Drew Benjamin Sinha

McKelvey School of Engineering Theses & Dissertations

Aging decline is a universal and unescapable phenomenon; as organisms reach maturity and continue living, physiological function inevitably declines, resulting in mortality. While the study of mortality has been long studied, technical and practical challenges have limited the equally important study of how/when individuals deteriorate and what types of factors affect that deterioration. This gap in knowledge is not only evident in a relative lack of empirical data on physiological decline, but considerable debate around the analysis and conceptual interpretations of the little data that is available.

In this dissertation, I use quantitative reasoning and analysis of longitudinal data to …

Keystroke Dynamics Based On Machine Learning, Han-Chih Chang

Master's Projects

The development of active and passive biometric authentication and identification technology plays an increasingly important role in cybersecurity. Biometrics that utilize features derived from keystroke dynamics have been studied in this context. Keystroke dynamics can be used to analyze the way that a user types by monitoring various keyboard inputs. Previous work has considered the feasibility of user authentication and classification based on keystroke features. In this research, we analyze a wide variety of machine learning and deep learning models based on keystroke-derived features, we optimize the resulting models, and we compare our results to those obtained in related research. …

Facial Recognition And Face Mask Detection Using Machine Learning Techniques, Mira M. Boulos

Theses, Dissertations and Culminating Projects

Facial recognition, as a biometric system, is a crucial tool for the identification procedures. When using facial recognition, an individual's identity is identified using their unique facial features. Biometric authentication system helps in identifying individuals using their physiological and behavioral features. Physiological biometrics utilize human features such as faces, irises, and fingerprints. In contrast, behavioral biometric rely on features that humans do, such as voice and handwritings. Facial recognition has been widely used for security and other law enforcement purposes. However, since COVID-19 pandemic, many people around the world had to wear face masks. This thesis introduces a neural network …

Assessing The Re-Identification Risk In Ecg Datasets And An Application Of Privacy Preserving Techniques In Ecg Analysis, Arin Ghazarian

Computational and Data Sciences (PhD) Dissertations

In this work, first we investigate the use of ECG signal as a biometric in human identification systems using deep learning models. We train convolutional neural network models on ECG samples from approximately 81k patients. Our models achieved an over-all accuracy of 95.69%. Further, we assess the accuracy of our ECG identification model for distinct groups of patients with particular heart conditions and combinations of such conditions. For example, we observed that the identification accuracy was the highest (99.7%) for patients with both ST changes and supraventricular tachycardia. On the other hand, we also found that the identification rate was …

Poisoning Attacks On Learning-Based Keystroke Authentication And A Residue Feature Based Defense, Zibo Wang

Doctoral Dissertations

Behavioral biometrics, such as keystroke dynamics, are characterized by relatively large variation in the input samples as compared to physiological biometrics such as fingerprints and iris. Recent advances in machine learning have resulted in behaviorbased pattern learning methods that obviate the effects of variation by mapping the variable behavior patterns to a unique identity with high accuracy. However, it has also exposed the learning systems to attacks that use updating mechanisms in learning by injecting imposter samples to deliberately drift the data to impostors’ patterns. Using the principles of adversarial drift, we develop a class of poisoning attacks, named Frog-Boiling …

Biochemical And Chemical Methods Of Key Derivation For Cryptographic Ciphers, Leif K. Mcgoldrick

Legacy Theses & Dissertations (2009 - 2024)

Cryptography is a vital component of digital communication and digital data in general. The use of cryptography is necessary to support the veracity of data and to protect it from outside parties with malicious intent. Cryptography focuses on two main facets that are vital for this goal: data encryption and user authentication. Encryption protects the data by transforming it into an encrypted text that would not allow someone access without having or breaking the encryption method that was used to make it. User authentication is a multiple part process that allows for one to be able to identify oneself to …

Parsimonious Covariate Selection For Interval Censored Data, Yi Cui

Legacy Theses & Dissertations (2009 - 2024)

Interval censored outcomes widely arise in many clinical trials and observational studies. In many cases, subjects are only followed-up periodically. As a result, the event of interest is known only to occur within a certain interval. We provided a method to select the parsimonious set of covariates associated with the interval censored outcome. First, the iterative sure independence screening (ISIS) method was applied to all interval censored time points across subjects to simultaneously select a set of potentially important covariates; then multiple testing approaches were used to improve the selection accuracy through refining the selection criteria, i.e. determining a refined …

Bioaffinity-Based Methods For Forensic, Biometric, And Clinical Purposes, Mindy Elizabeth Hair

Legacy Theses & Dissertations (2009 - 2024)

Biomarker analysis is a well-established discipline that involves the evaluation of biological samples for the presence of various substances indicative of personal attributes or illnesses. Sweat is one example of a biological fluid that is often overlooked for forensic and clinical analyses, even though it can contain DNA, various amino acids, and other low molecular weight compounds.1–3 The work presented in this dissertation focuses on the use of bioaffinity-based assays to quantify biomarkers in sweat for both forensic and clinical applications. The concentration of the biochemical content within an individual’s sweat are controlled by hormone-based metabolic pathways4 that fluctuate daily …

Speaker Recognition Using Machine Learning Techniques, Abhishek Manoj Sharma

Master's Projects

Speaker recognition is a technique of identifying the person talking to a machine using the voice features and acoustics. It has multiple applications ranging in the fields of Human Computer Interaction (HCI), biometrics, security, and Internet of Things (IoT). With the advancements in technology, hardware is getting powerful and software is becoming smarter. Subsequently, the utilization of devices to interact effectively with humans and performing complex calculations is also increasing. This is where speaker recognition is important as it facilitates a seamless communication between humans and computers. Additionally, the field of security has seen a rise in biometrics. At present, …

Orientation Invariance Methods For Inertial Gait, Ravichandran Subramanian

USF Tampa Graduate Theses and Dissertations

Intelligent devices such as smart phones, smart watches, virtual reality (VR) headsets and personal exercise devices have become integral elements of accessories used by many people. The ability of these devices to verify or identify the user could be applied for enhanced security and user experience customization among other things. Almost all these devices have built-in inertial sensors such as accelerometer and gyroscope. These inertial sensors respond to the movements made by the user while performing day to day activities like walking, getting up and sitting down. The response depends on the activity being performed and thus can be used …

Use Of Biometrics To Determine Biochemistry Knowledge Level Differences In Reading And Processing Metabolic Pathways, Kim Kammerdiener

Master of Science in Chemical Sciences Theses

The areas of chemistry and biochemistry commonly use external representations to enhance learning for students. The use of schematics and representations for illustrating metabolic pathways is a familiar image in most biochemistry textbooks. These external representations can be the key to student understanding. To date, there has not been any previous research specifically focused on the areas of interest that are predominant for an individual viewing a metabolic pathway commonly found in a biochemistry textbook. Therefore, this thesis study set out to 1) investigate what individuals look at in a metabolic pathway based on their level of expertise in metabolism …

Identification Of Individuals From Ears In Real World Conditions, Earnest Eugene Hansley

USF Tampa Graduate Theses and Dissertations

A number of researchers have shown that ear recognition is a viable alternative to more common biometrics such as fingerprint, face and iris because the ear is relatively stable over time, the ear is non-invasive to capture, the ear is expressionless, and both the ear’s geometry and shape have significant variation among individuals. Researchers have used different approaches to enhance ear recognition. Some researchers have improved upon existing algorithms, some have developed algorithms from scratch to assist with recognizing individuals by ears, and some researchers have taken algorithms tried and tested for another purpose, i.e., face recognition, and applied them …

Multimodal Sensing And Data Processing For Speaker And Emotion Recognition Using Deep Learning Models With Audio, Video And Biomedical Sensors, Farnaz Abtahi

Dissertations, Theses, and Capstone Projects

The focus of the thesis is on Deep Learning methods and their applications on multimodal data, with a potential to explore the associations between modalities and replace missing and corrupt ones if necessary. We have chosen two important real-world applications that need to deal with multimodal data: 1) Speaker recognition and identification; 2) Facial expression recognition and emotion detection.

The first part of our work assesses the effectiveness of speech-related sensory data modalities and their combinations in speaker recognition using deep learning models. First, the role of electromyography (EMG) is highlighted as a unique biometric sensor in improving audio-visual speaker …

Medical Identity Theft And Palm Vein Authentication: The Healthcare Manager's Perspective, Cruz Cerda Iii

Walden Dissertations and Doctoral Studies

The Federal Bureau of Investigation reported that cyber actors will likely increase cyber intrusions against healthcare systems and their concomitant medical devices because of the mandatory transition from paper to electronic health records, lax cyber security standards, and a higher financial payout for medical records in the deep web. The problem addressed in this quantitative correlational study was uncertainty surrounding the benefits of palm vein authentication adoption relative to the growing crime of medical identity theft. The purpose of this quantitative correlational study was to understand healthcare managers' and doctors' perceptions of the effectiveness of palm vein authentication technology. The …

Analysis Of Affective State As Covariate In Human Gait Identification, Kofi Agyemang Adumata

Walden Dissertations and Doctoral Studies

There is an increased interest in the need for a noninvasive and nonintrusive biometric identification and recognition system such as Automatic Gait Identification (AGI) due to the rise in crime rates in the US, physical assaults, and global terrorism in public places. AGI, a biometric system based on human gait, can recognize people from a distance and current literature shows that AGI has a 95.75% success rate in a closely controlled laboratory environment. Also, this success rate does not take into consideration the effect of covariate factors such as affective state (mood state); and literature shows that there is a …

Uface: Your Universal Password No One Can See, Nicholas Steven Hilbert

Masters Theses

"With the advantage of not having to memorize long passwords, facial authentication has become a topic of interest among researchers. However, since many users store images containing their face on social networking sites, a new challenge emerges in preventing attackers from impersonating these users by using these online photos. Another problem with most current facial authentication protocols is that they require an unencrypted image of each registered user's face to compare against. Moreover, they might require the user's device to execute computationally expensive multiparty protocols which presents a problem for mobile devices with limited processing power. Finally, these authentication protocols …

Biometrics-Based Dynamic Authentication For Secure Services, Saif Mohammed Saeed Abdulla Al Aryani

Theses

This thesis proposes a secure authentication protocol against physical session hijacking attacks. In client/server technology, users establish sessions to access the services offered by the servers. However, using physical session hijacking attacks, malicious users may physically take control of ongoing sessions. Malicious users also can establish sessions with servers using stolen passwords. In both cases, the server will be communicating with the wrong user who pretends to be the real user. The goal of this authentication protocol is to continuously and dynamically ensure that during an ongoing session the current session’s user is himself the real person that is known …

An Empirical Investigation Of Factors Affecting Resistance To Using Multi-Method Authentication Systems In Public-Access Environments, Joseph Marnell

CCE Theses and Dissertations

Over the course of history, different means of object and person identification as well as verification have evolved for user authentication. In recent years, a new concern has emerged regarding the accuracy of verifiable authentication and protection of personal identifying information (PII), because previous misuses have resulted in significant financial loss. Such losses have escalated more noticeably because of human identity-theft incidents due to breaches of PII within multiple public-access environments. Although the use of various biometric and radio frequency identification (RFID) technologies is expanding, resistance to using these technologies for user authentication remains an issue. This study addressed the …

A Dynamic Behavioral Biometric Approach To Authenticate Users Employing Their Fingers To Interact With Touchscreen Devices, Arturo Ponce

CCE Theses and Dissertations

The use of mobile devices has extended to all areas of human life and has changed the way people work and socialize. Mobile devices are susceptible to getting lost, stolen, or compromised. Several approaches have been adopted to protect the information stored on these devices. One of these approaches is user authentication. The two most popular methods of user authentication are knowledge based and token based methods but they present different kinds of problems.

Biometric authentication methods have emerged in recent years as a way to deal with these problems. They use an individual’s unique characteristics for identification and have …

An Electroencephalogram (Eeg) Based Biometrics Investigation For Authentication: A Human-Computer Interaction (Hci) Approach, Ricardo J. Rodriguez

CCE Theses and Dissertations

Encephalogram (EEG) devices are one of the active research areas in human-computer interaction (HCI). They provide a unique brain-machine interface (BMI) for interacting with a growing number of applications. EEG devices interface with computational systems, including traditional desktop computers and more recently mobile devices. These computational systems can be targeted by malicious users. There is clearly an opportunity to leverage EEG capabilities for increasing the efficiency of access control mechanisms, which are the first line of defense in any computational system.

Access control mechanisms rely on a number of authenticators, including “what you know”, “what you have”, and “what you …

Evaluating The Long-Term Effects Of Logging Residue Removals In Great Lakes Aspen Forests, Michael I. Premer

Dissertations, Master's Theses and Master's Reports

Commercial aspen (Populus spp.) forests of the Great Lakes region are primarily managed for timber products such as pulp fiber and panel board, but logging residues (topwood and non-merchantable bolewood) are potentially important for utilization in the bioenergy market. In some regions, pulp and paper mills already utilize residues as fuel in combustion for heat and electricity, and progressive energy policies will likely cause an increase in biomass feedstock demand. The effects of removing residues, which have a comparatively high concentration of macronutrients, is poorly understood when evaluating long-term site productivity, future timber yields, plant diversity, stand dynamics, and …

Gender And Ethnicity Classification Using Partial Face In Biometric Applications, Jamie Lyle

All Dissertations

As the number of biometric applications increases, the use of non-ideal information such as images which are not strictly controlled, images taken covertly, or images where the main interest is partially occluded, also increases. Face images are a specific example of this. In these non-ideal instances, other information, such as gender and ethnicity, can be determined to narrow the search space and/or improve the recognition results. Some research exists for gender classification using partial-face images, but there is little research involving ethnic classifications on such images. Few datasets have had the ethnic diversity needed and sufficient subjects for each ethnicity …

Ear Contour Detection And Modeling Using Statistical Shape Models, Satish Ravindran

All Theses

Ear detection is an actively growing area of research because of its applications in human head tracking and biometric recognition. In head tracking, it is used to augment face detectors and to perform pose estimation. In biometric systems, it is used both as an independent modality and in multi-modal biometric recognition. The ear shape is the preferred feature used to perform detection because of its unique structure in both 2D color images and 3D range images. Ear shape models have also been used in literature to perform ear detection, but at a cost of a loss in information about the …

Vulnerability Analysis Of Cyber-Behavioral Biometric Authentication, Abdul Serwadda

Doctoral Dissertations

Research on cyber-behavioral biometric authentication has traditionally assumed naïve (or zero-effort) impostors who make no attempt to generate sophisticated forgeries of biometric samples. Given the plethora of adversarial technologies on the Internet, it is questionable as to whether the zero-effort threat model provides a realistic estimate of how these authentication systems would perform in the wake of adversity. To better evaluate the efficiency of these authentication systems, there is need for research on algorithmic attacks which simulate the state-of-the-art threats.

To tackle this problem, we took the case of keystroke and touch-based authentication and developed a new family of algorithmic …