Computer Sciences Commons^™

On Phishing: Proposing A Host-Based Multi-Layer Passive/Active Anti-Phishing Approach Combating Counterfeit Websites, Wesam Harbi Fadheel

Dissertations

Phishing is the starting point of most cyberattacks, mainly categorized as Email, Websites, Social Networks, Phone calls (Vishing), and SMS messaging (Smishing). Phishing refers to an attempt to collect sensitive data, typically in the form of usernames, passwords, credit card numbers, bank account information, etc., or other crucial facts, intending to use or sell the information obtained. Similar to how a fisherman uses bait to catch a fish, an attacker will pose as a trustworthy source to attract and deceive the victim.

This study explores the efficacy of host-side APT (Anti-Phishing Techniques) based onWebsite features like Lexical, Host-Based, or Content-Based …

Evaluating Learning Geometric Concepts To Generate Predicate Abstract Domains In Static Program Analysis, Patrick Chadbourne

Boise State University Theses and Dissertations

Accuracy of static analysis over predicate abstract domains depends on the partitions of predicates. More precise predicates approximate concrete values of program variables resulting in more accurate analysis. Manual reasoning about these partitions must be done on a case-by-case basis and is time consuming and difficult.

This work explores learning geometric concepts to automate discovery of predicate domain candidates.

The proposed framework uses run-time data from program executions to gather training data for a PAC-learner to generate separating hyperplanes that can be projected onto predicate domains.

The thesis implements the framework and performs evaluations of it effectiveness on a set …

Robust Digital Nucleic Acid Memory, Golam Md Mortuza

Boise State University Theses and Dissertations

The rapid growth of data generation from electronic devices has created a critical demand for efficient and sustainable data storage solutions. Traditional storage systems face challenges regarding reliability, energy consumption, and scalability, necessitating the exploration of alternative technologies. This dissertation explores the potential of Deoxyribonucleic Acid (DNA) as an alternative storage medium, along with the associated challenges and potential solutions.

This dissertation focuses on Digital Nucleic Acid Memory (dNAM), which utilizes Single Molecule Localization Microscopy (SMLM) to encode and store data within DNA structures called DNA origami. SMLM surpasses the limitations of light’s diffraction limit, enabling the imaging of biological …

Risk Assessment And Solutions For Two Domains: Election Procedures And Privacy Disclosure Prevention For Users, Kamryn Deann Parker

Boise State University Theses and Dissertations

Risk is something that surrounds us each and every day, and learning how to manage risk in different areas is necessary to limit its impact. Two different areas of risk have been identified for this thesis: election day incident infrastructure and user privacy disclosure prevention. We ask if it is possible to leverage information related to risk to create procedures that handle it as an overall issue in order to apply procedures to similar areas of research. Understanding how to identify and prevent these potential areas of risk is important to secure information not just for a single person, but …

Fair Layouts In Information Access Systems: Provider-Side Group Fairness In Ranking Beyond Ranked Lists, Amifa Raj

Boise State University Theses and Dissertations

Information access systems, such as search engines and recommender systems, often display results in ranked order based on their estimated relevance. The fairness of these rankings has received attention as an important evaluation criteria along with traditional metrics capturing constructs such as utility or accuracy. Fairness has many facets, including provider and consumer-side fairness at both group and individual levels. Research on provider-side group fairness involve concerns regarding measurement and optimization of fairness in ranking. Although there are several fair ranking metrics to measure provider-side group fairness based on various “sensitive attributes”, multiple open challenges still exist in this area …

Virtual Curtain: A Communicative Fine-Grained Privacy Control Framework For Augmented Reality, Aakash Shrestha

Boise State University Theses and Dissertations

Augmented Reality (AR) technologies have advanced significantly due to continuous sensing technology and ongoing advancements in mobile technologies such as device portability, camera quality, and system performance. Continuous sensing technology is the key to enabling an AR experience. However, untrusted applications leverage continued access to these sensor data, posing significant privacy concerns for both AR users and bystanders. The rapid growth of AR devices has resulted in broad commercialization and daily use. As a newer field, many users are unaware of the potential privacy risks these AR devices pose due to unintended information leakage. As a result, a privacy control …

Transformer Reinforcement Learning Approach To Attack Automatic Fake News Detectors, Chandler Underwood

Boise State University Theses and Dissertations

Misinformation and disinformation disguised in the form of fake news stories have garnered a lot of attention as of late largely because they confuse and often anger the public, leading to a less cohesive society for us all. In response to the ever-growing issue of fake news stories circulating on social media, researchers have crafted various solutions to predict the veracity of stories in hopes of catching illegitimate ones before they can spread. In response to this research area, a newer research area focused on attacking fake news detectors is forming. In this work we have built an adversarial text …

Facial Expression Recognition Using Convolutional Neural Networks (Cnns) And Generative Adversarial Networks (Gans) For Data Augmentation And Image Generation, Shekhar Singh

UNLV Theses, Dissertations, Professional Papers, and Capstones

Facial expressions play a crucial role in human communication, serving as a powerful means to convey emotions. However, classifying facial expressions using artificial intelligence (AI) can be challenging, especially with small datasets and images. Facial Expression Recognition (FER) is an active area of research, with Convolutional Neural Networks (CNNs) being widely employed for classification. In this research, we propose a CNN-based approach for FER that utilizes both original and augmented datasets to enhance classification accuracy. Experimental results on the FER2013 dataset show test accuracies of 63.39% and 64.59% for the original and augmented datasets, respectively, in a seven-class classification task. …

Physics-Guided Deep Learning For Solar Wind Modeling At L1 Point, Robert M. Johnson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Neural networks are adept at finding patterns that are too long and too small for humans to find in data. Usually, this power is used to generate predictions with greater accuracy than most alternative models. However, we can also use this power to understand more about the data we train these networks on. We do this by changing the data that the networks train on and the data they are tested on. This allows us to both control the maximum length of a pattern and to compare data between different groups, in our case, different solar cycles. This thesis is …

Comparative Study Of Clustering Techniques On Eye-Tracking In Dynamic 3d Virtual Environments, Scott Johnson

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Eye-tracking has been used for decades to understand how and why an individual focuses on particular objects, areas, and elements of space. A vast body of knowledge exists on how eye-tracking is measured. However, historically, eye-tracking has been predominately studied using 2D environments, with limited work in 3D environments. The purpose of this study is to identify which methods most accurately represent the areas that have captured the participant’s visual attention within a 3D dynamic environment. This will be completed by evaluating different clustering methods of fixations using a customized virtual reality tool that collects eye-tracking data. There exist several …

Generalizing Deep Learning Methods For Particle Tracing Using Transfer Learning, Shubham Gupta

All Graduate Theses and Dissertations, Spring 1920 to Summer 2023

Particle tracing is a very important method for scientific visualization of vector fields, but it is computationally expensive. Deep learning can be used to speed up particle tracing, but existing deep learning models are domain-specific. In this work, we present a methodology to generalize the use of deep learning for particle tracing using transfer learning. We demonstrate the performance of our approach through a series of experimental studies that address the most common simulation design scenarios: varying time span, Reynolds number, and problem geometry. The results show that our methodology can be effectively used to generalize and accelerate the training …

Mechanisms To Reduce Cyber Threats And Risks, Saad Alsuwaileh

Journal of Police and Legal Sciences

Addressing the mechanisms of reducing cyber threats and risks Research Because cyberspace is an important arena for various international interactions, especially in recent times in light of the increase in cyber-attacks between some countries, which affects their national security. In this context, many countries are trying to make an effort to develop their capabilities to be used in any cyber-attack, or to take adequate preventive measures to protect them from any possible cyberattacks, especially in light of the impact of these attacks on vital places and institutions such as banks and ministries or on important facilities such as water and …

The Role Of The Family In Confronting The Excessive Use Of Modern Technology Among Children "Therapeutic Alternatives", Khaled Mikhlif Al-Jenfawi

Journal of Police and Legal Sciences

This study aimed to identify the role of the family in confronting the excessive use of technology and social media programs from the view point of social workers and psychologists working for the Juvenile Welfare Department of the Ministry of Social Affairs and Labor in Kuwait, in the light of some variables (sex , and practical experience)

The studywas a descriptive analytical study. It used the social survey method. A questionnaire consisting of (39) items was built and designed, and its validity and reliability were tested. Among the most important results of the study: The level of the family's role …

Analysis Of The Main Factor In The Implementation Of Open Defecation Free Using The Ahp Method, Vica Asrianti Dwiputri, Ova Candra Dewi

Smart City

Environmental sanitation refers to an environment's health status, including housing, sewage disposal, clean water supply, waste management, and other factors. Sustainable Development Goals 6 (SDG 6) ensures people access proper environmental sanitation. Based on the monitoring and evaluation results of Community-Based Total Sanitation (STBM) in 2022, it was found that 100% of open defecation had been stopped for Pillar 1 of STBM. This study aims to identify the factors that influence the success of implementing Open Defecation Free (ODF) programs in Depok City. There are two stages in this study to determine the priority factors that influence the success of …

Neutrosophic Gsα* - Open And Closed Maps In Neutrosophic Topological Spaces, P. Anbarasi Rodrigo, S. Maheswari

Neutrosophic Systems with Applications

The main aim of this paper is to introduce a new concept of Neu-mapping namely Neugsa*-open maps and Neugsa* -closed maps in Neu-topological spaces. Additionally, we relate the properties and characterizations of these mappings with the other mappings in Neu-topological spaces.

Artificial Intelligence Frameworks To Detect And Investigate The Pathophysiology Of Spaceflight Associated Neuro-Ocular Syndrome (Sans), Joshua Ong, Ethan Waisberg, Mouayad Masalkhi, Sharif Amit Kamran, Kemper Lowry, Prithul Sarker, Nasif Zaman, Phani Paladugu, Alireza Tavakkoli, Andrew G Lee

Student Papers, Posters & Projects

Spaceflight associated neuro-ocular syndrome (SANS) is a unique phenomenon that has been observed in astronauts who have undergone long-duration spaceflight (LDSF). The syndrome is characterized by distinct imaging and clinical findings including optic disc edema, hyperopic refractive shift, posterior globe flattening, and choroidal folds. SANS serves a large barrier to planetary spaceflight such as a mission to Mars and has been noted by the National Aeronautics and Space Administration (NASA) as a high risk based on its likelihood to occur and its severity to human health and mission performance. While it is a large barrier to future spaceflight, the underlying …

Neutrosophic Gsα* - Open And Closed Maps In Neutrosophic Topological Spaces, P. Anbarasi Rodrigo, S. Maheswari

Neutrosophic Systems with Applications

The main aim of this paper is to introduce a new concept of Neu-mapping namely Neugsa*-open maps and Neugsa* -closed maps in Neu-topological spaces. Additionally, we relate the properties and characterizations of these mappings with the other mappings in Neu-topological spaces.

Accuracy Vs. Energy: An Assessment Of Bee Object Inference In Videos From On-Hive Video Loggers With Yolov3, Yolov4-Tiny, And Yolov7-Tiny, Vladimir A. Kulyukin, Aleksey V. Kulyukin

Computer Science Faculty and Staff Publications

A continuing trend in precision apiculture is to use computer vision methods to quantify characteristics of bee traffic in managed colonies at the hive's entrance. Since traffic at the hive's entrance is a contributing factor to the hive's productivity and health, we assessed the potential of three open-source convolutional network models, YOLOv3, YOLOv4-tiny, and YOLOv7-tiny, to quantify omnidirectional traffic in videos from on-hive video loggers on regular, unmodified one- and two-super Langstroth hives and compared their accuracies, energy efficacies, and operational energy footprints. We trained and tested the models with a 70/30 split on a dataset of 23,173 flying bees …

Self-Supervised Learning Application On Covid-19 Chest X- Ray Image Classification Using Masked Autoencoder, Xin Xing, Gongbo Liang, Chris Wang, Nathan Jacobs, Ai-Ling Lin

All Faculty Scholarship (Archived)

The COVID-19 pandemic has underscored the urgent need for rapid and accurate diagnosis facilitated by artificial intelligence (AI), particularly in computer-aided diagnosis using medical imaging. However, this context presents two notable challenges: high diagnostic accuracy demand and limited availability of medical data for training AI models. To address these issues, we proposed the implementation of a Masked AutoEncoder (MAE), an innovative self-supervised learning approach, for classifying 2D Chest X-ray images. Our approach involved performing imaging reconstruction using a Vision Transformer (ViT) model as the feature encoder, paired with a custom-defined decoder. Additionally, we fine-tuned the pretrained ViT encoder using a …

Towards Crisp‐Bc: 3tic Specification Framework For Blockchain Use‐Cases, Pouyan Jahanbin, Ravi S. Sharma, Stephen T. Wingreen, Nir Kshetri, Kim‐Kwang Raymond Choo

All Works

The application of Blockchain and augmented technologies such as IoT, AI, and Big Data platforms present a feasible approach for resolving the implementation challenges of trusted, decentralized platforms. This article proposes a DevOps framework for the specification of Blockchain use‐cases that enables evaluation, replication, and benchmarking. Specifically, it could be applied to specify the requirements and design characteristics of Blockchain applications in terms of key attributes such as: (i) transparency; (ii) traceability; (iii) tamper‐resistance; (iv) immutability; and (v) compliance. The article first introduces the design characteristics of Blockchain as a Platform and then examines successful use‐cases for its implementation using …

Integrating External Sensors With Crazyflie Drones, Xiaowen Wang, Dheryta Jaisinghani, Andrew Berns

Summer Undergraduate Research Program (SURP) Symposium

• Drones are widely used: Mini drones such as Crazyflie 2.1 are used in a variety of fields.
• Grove Sound Sensor function: Grove Sound Sensor can capture sound, providing more application possibilities for drones.
• The potential of Crazyflie 2.1: Although Crazyflie 2.1 has the potential to be an integrated sensor platform, prior to this project, it was uncertain whether sensors could be connected on it.
• Project motivation: Our project aims to explore whether Crazyflie 2.1 can be connected to the Grove Sound Sensor and collect and process data from the sensor.
• Impact of the project: If successful, this project will open …

Watermark Hiding In Hdr Image Based On Visual Saliency And Tucker Decomposition, Roa'a M. Al-Airaji, Ibtisam A. Aljazaery, Haider Th. Salim Alrikabi

Karbala International Journal of Modern Science

Recently, great attention has been paid to high dynamic range (HDR) images because of their richly detailed and high dynamic range of intensity. The need for pre-processing of the HDR image format with tone mapping (TM) operators makes it unique; the TM operators are provided on display with a low dynamic range (LDR). On the other hand, TM can be regarded as an inevitable attack when protecting HDR image ownership is considered. An adaptive approach for concealing watermarks based on visual saliency and Tucker decomposition has been presented in this article. In the first step, three feature maps were produced …

An Investigative Study On Quick Switching System Using Fuzzy And Neutrosophic Poisson Distribution, Uma G, Nandhitha S

Neutrosophic Systems with Applications

Stephens and Larson (1967) stated the sampling system as an allotted grouping of two or three sampling plans and the rules for switching between the plans for sentencing the lots of manufactured products. Quick Switching System (QSS) by Romboski (1969) is a sampling system with reference to the Single Sampling Plan (SSP) involves normal and tightened plans by adopting a switching rule. QSS provides quality protection and a reduction in the cost of inspection. The idea of fuzzy logic is adopted in the system to handle situations of fraction non-confirmation, uncertainty, or vagueness present in the parameters. The sampling plans …

An Investigative Study On Quick Switching System Using Fuzzy And Neutrosophic Poisson Distribution, Uma G, Nandhitha S

Neutrosophic Systems with Applications

Stephens and Larson (1967) stated the sampling system as an allotted grouping of two or three sampling plans and the rules for switching between the plans for sentencing the lots of manufactured products. Quick Switching System (QSS) by Romboski (1969) is a sampling system with reference to the Single Sampling Plan (SSP) involves normal and tightened plans by adopting a switching rule. QSS provides quality protection and a reduction in the cost of inspection. The idea of fuzzy logic is adopted in the system to handle situations of fraction non-confirmation, uncertainty, or vagueness present in the parameters. The sampling plans …

Forensic Investigation Of Small-Scale Digital Devices: A Futuristic View, Farkhund Iqbal, Aasia Jaffri, Zainab Khalid, Aine Macdermott, Qazi Ejaz Ali, Patrick C. K. Hung

All Works

Small-scale digital devices like smartphones, smart toys, drones, gaming consoles, tablets, and other personal data assistants have now become ingrained constituents in our daily lives. These devices store massive amounts of data related to individual traits of users, their routine operations, medical histories, and financial information. At the same time, with continuously evolving technology, the diversity in operating systems, client storage localities, remote/cloud storages and backups, and encryption practices renders the forensic analysis task multi-faceted. This makes forensic investigators having to deal with an array of novel challenges. This study reviews the forensic frameworks and procedures used in investigating small-scale …

Fostering Human Dimension Of Smart Cities: Lessons From Jakarta For Nusantara, Indonesia’S New Capital City In The Making, Wicaksono Sarosa, Nurulitha Andini Susetyo, Marsa Nur Aulianisa, Mahbub Ridhoo Maulaa, Pradamas Giffary

Smart City

A city’s problems often arise as the population grows and urbanization happens. This process is linear to the development of information-and-communication technologies (ICT), especially in urban areas. As a result, cities have adopted an initiative to solve the problems which are popularly known as the smart city. Over decades, the idea of a smart city has evolved from a mere technological modernization to advanced utilization through community involvement. However, in practice, smart city ideas and initiatives often put a heavy emphasis on technical aspects and ignored the more human side, which has caused a digital divide. This paper argues that …

Cytochrome P450 Gene Families: Role In Plant Secondary Metabolites Production And Plant Defense, Panchali Chakraborty, Ashok Biswas, Susmita Dey, Tuli Bhattacharjee, Swapan Chakrabarty

Michigan Tech Publications

Cytochrome P450s (CYPs) are the most prominent family of enzymes involved in NADPH- and O2-dependent hydroxylation processes throughout all spheres of life. CYPs are crucial for the detoxification of xenobiotics in plants, insects, and other organisms. In addition to performing this function, CYPs serve as flexible catalysts and are essential for producing secondary metabolites, antioxidants, and phytohormones in higher plants. Numerous biotic and abiotic stresses frequently affect the growth and development of plants. They cause a dramatic decrease in crop yield and a deterioration in crop quality. Plants protect themselves against these stresses through different mechanisms, which are accomplished by …

Prompt-Based Tuning Of Transformer Models For Multi-Center Medical Image Segmentation Of Head And Neck Cancer, Numan Saeed, Muhammad Ridzuan, Roba Al Majzoub, Mohammad Yaqub

Computer Vision Faculty Publications

Medical image segmentation is a vital healthcare endeavor requiring precise and efficient models for appropriate diagnosis and treatment. Vision transformer (ViT)-based segmentation models have shown great performance in accomplishing this task. However, to build a powerful backbone, the self-attention block of ViT requires large-scale pre-training data. The present method of modifying pre-trained models entails updating all or some of the backbone parameters. This paper proposes a novel fine-tuning strategy for adapting a pretrained transformer-based segmentation model on data from a new medical center. This method introduces a small number of learnable parameters, termed prompts, into the input space (less than …

Understanding Political Polarization Using Language Models: A Dataset And Method, Samiran Gode, Supreeth Bare, Bhiksha Raj, Hyungon Yoo

Natural Language Processing Faculty Publications

Our paper aims to analyze political polarization in US political system using language models, and thereby help candidates make an informed decision. The availability of this information will help voters understand their candidates' views on the economy, healthcare, education, and other social issues. Our main contributions are a dataset extracted from Wikipedia that spans the past 120 years and a language model-based method that helps analyze how polarized a candidate is. Our data are divided into two parts, background information and political information about a candidate, since our hypothesis is that the political views of a candidate should be based …

Multi-Scale Attention Networks For Pavement Defect Detection, Junde Chen, Yuxin Wen, Yaser Ahangari Nanehkaran, Defu Zhang, Adan Zeb

Engineering Faculty Articles and Research

Pavement defects such as cracks, net cracks, and pit slots can cause potential traffic safety problems. The timely detection and identification play a key role in reducing the harm of various pavement defects. Particularly, the recent development in deep learning-based CNNs has shown competitive performance in image detection and classification. To detect pavement defects automatically and improve effects, a multi-scale mobile attention-based network, which we termed MANet, is proposed to perform the detection of pavement defects. The architecture of the encoder-decoder is used in MANet, where the encoder adopts the MobileNet as the backbone network to extract pavement defect features. …