Digital Commons Network^™

The Identification Of Rogue Access Points Using Channel State Information, Irene Mcginniss

Theses, Dissertations and Culminating Projects

Today's wireless networks (Wi-Fi) handle more significant numbers of connections, deploy efficiently, and provide increased reliability and high speeds at low cost. The ability of rogue access points (RAPs) to mimic legitimate APs makes them the most critical threat to wireless security. APs are found in coffee shops, supermarkets, stadiums, buses, trains, airports, hospitals, theaters, and shopping malls.

Rogue access points (RAP) are unauthorized devices that connect to legitimate access points and networks and bypass authorized security procedures. RAP detection has been attempted using hardware and software-based solutions requiring the developing of dedicated tools or beacon frame modification. (Arisandi, 2021). …

The Construction Of A Static Source Code Scanner Focused On Sql Injection Vulnerabilties In Java, Carla Zurita Rubin De Celis

Theses, Dissertations and Culminating Projects

SQL injection attacks are a significant threat to web application security, allowing attackers to execute arbitrary SQL commands and gain unauthorized access to sensitive data. Static source code analysis is a widely used technique to identify security vulnerabilities in software, including SQL injection attacks. However, existing static source code scanners often produce false positives and require a high level of expertise to use effectively. This thesis presents the design and implementation of a static source code scanner for SQL injection vulnerabilities in Java queries. The scanner uses a combination of pattern matching and data flow analysis to detect SQL injection …

Object Detection And Image Categorization By Transferring Commonsense Knowledge With Premises And Quantifiers, Irina Chernyavsky

Theses, Dissertations and Culminating Projects

Domestic, or household robots, are autonomous robots designed to make our home-life easier by performing chores and mundane tasks such as cleaning, or cooking. Currently domestic robots are specialized to complete a specific task and, therefore, are confined by factors such as mobility, size, and complexity. With the fast development of computer vision and robotics, the need for more compact, advanced and multi-task robots has emerged. Therefore, the robot needs to be multi-functional, able to discern the environment and the tasks. The aim of this paper is to categorize images in domestic robots as relevant to the culinary, laundry, vacuum …

A Functioning Code May Not Be A Secure Code : A Preliminary Study On The Students' Complacency With Secure Coding, Jeremiah Niiquaye Kotey

Theses, Dissertations and Culminating Projects

Eleanor Roosevelt once said: "Learn from the mistakes of others. You can’t live long enough to make them all yourself". Mistakes are almost inevitable while coding or designing a system. Therefore, patches are created to fix the issues in the code either by a manual review, or through a static analysis tool. Oftentimes, mistakes in programming emanate from lack of skills thus, competence with a particular programming language but negligence also plays a role in other instances. A functioning code that solves a particular problem does not guarantee that the code is secure, hence the code should be structured to …

Privacy-Enhanced And Outsourced Power Usage Control In Smart Grids, Hemadri Patel

Theses, Dissertations and Culminating Projects

Due to the numerous advantages of smart grids like reliability, availability, and efficiency, it has been emerging as an extraordinary contribution to the economic and environmental health. This project mainly focuses on the power outage issue in a smart grid environment. Power outages occur when electricity demand exceeds the supply, more specifically, consider a utility company which sets a threshold on the total power usage of households from a neighborhood. Whenever the total power usage from a neighborhood exceeds the threshold, some of the households needs to reduce their energy consumption; to avoid the power outage. This problem is referred …

Secure Retrieval Of Encrypted Similar Documents Using Bloom Filters, German Guzman

Theses, Dissertations and Culminating Projects

The ability to search for similar documents is a well-known problem on the Web and Information Retrieval field. For example, identifying similar profiles across different government agencies is an important process during intelligence gathering. Nonetheless, when data belongs to multiple parties, internal security policies and government regulations cannot allow the participating parties to freely share their sensitive documents. In our project, we aim to address the following problem: Given a user’s query Q and an encrypted database of documents stored on a third-party cloud server, we want to retrieve top-k documents similar to Q without disclosing Q and the contents …

Secrep : A Framework For Automating The Extraction And Prioritization Of Security Requirements Using Machine Learning And Nlp Techniques, Shada Khanneh

Theses, Dissertations and Culminating Projects

Gathering and extracting security requirements adequately requires extensive effort, experience, and time, as large amounts of data need to be analyzed. While many manual and academic approaches have been developed to tackle the discipline of Security Requirements Engineering (SRE), a need still exists for automating the SRE process. This need stems mainly from the difficult, error-prone, and time-consuming nature of traditional and manual frameworks. Machine learning techniques have been widely used to facilitate and automate the extraction of useful information from software requirements documents and artifacts. Such approaches can be utilized to yield beneficial results in automating the process of …

Studying Alive : An Application For The Wellness Of College Students During The Covid-19 Pandemic, Natasia Fernandez

Theses, Dissertations and Culminating Projects

Mental health awareness has become an increasingly important topic over the past couple of years due the Covid-19 pandemic. Many individuals find it difficult to discuss their mental health. An individual’s mental health is a significant factor in maintaining their overall wellness. College students, specifically, face various hurdles and challenges that can affect their mental health. They have several responsibilities weighing on their shoulders which can lead to stress, depression and/or anxiety. College students may find it difficult to express these topics and seek healthy ways to cope. During the Covid-19 pandemic, additional challenges have been added onto college students …

Identifying Functional And Non-Functional Software Requirements From User App Reviews And Requirements Artifacts, Dev Jayant Dave

Theses, Dissertations and Culminating Projects

This thesis proposes and evaluates Machine Learning (ML) based data models to identify and isolate software requirements from datasets containing user app review statements. The ML models classify user app review statements into Functional Requirements (FRs), Non-Functional Requirements (NFRs), and Non-Requirements (NRs). This proposed approach consisted of creating a novel hybrid dataset that contains software requirements from Software Requirements Specification (SRS) documents and user app reviews. The Support Vector Machine (SVM), Stochastic Gradient Descent (SGD), and Random Forest (RF) ML algorithms combined with the term frequency-inverse document frequency (TF-IDF) natural language processing (NLP) technique were implemented on the hybrid dataset. …

The Privacy Leakage Of Ip Camera Systems, Lee R. Castro

Theses, Dissertations and Culminating Projects

For in-home security, intelligent operations like top individual recognition and minimizing losses due to home break-ins, emergencies, and fraud are keys to success. This application integrates the closed-circuit television (CCTV) camera and the deep learning algorithms used to process these images. Automated intrusion detection alerts, real-time fire alerts, smart checkout, and potentially fraudulent point of sale (POS) transactions are its main features. Dynamic intrusion with machine learning is a software program in which the price of certain products changes over time through an algorithm that considers a variety of pricing variables. The face locator is a part of the algorithm …

Development And On-Road Applications Of A 1/10-Scale Autonomous Vehicle, Laura Cornejo Paulino

Theses, Dissertations and Culminating Projects

Autonomous vehicles (AVs) are a key component in the creation of the new transportation infrastructure. Over the last several decades, nations across the world have experienced an increase in traffic congestion, environmental deprecation due to greenhouse gas emissions and an increase in time loss and productivity. A key factor in these components is the increase in numbers of vehicles on the road, a number that continues to increase gradually every year. In addition, the continued increase in vehicles on the road poses a threat to human and environmental safety. There is strong evidence to support that accidental vehicular deaths and …

Towards Machine Learning-Based Demand Response Forecasting Using Smart Grid Data, Matthew S. Johnson

Theses, Dissertations and Culminating Projects

Demand response is a valuable tool for improving the reliability, stability, and financial efficiency of smart grids. With the intention of altering customer power consumption patterns, utility companies often implement strategies such as time-of-use (TOU) programs. Although effective in some situations, TOU programs struggle to perform in highly developed countries due to the complexity of human behavior. In this study, we analyze power consumption readings from smart meters from 5567 households in London, UK from November 2011 to February 2014 to measure the success of the TOU program. We additionally consider the variability of weather conditions and customer demographics when …

Time Of Flight And Fingerprinting Based Methods For Wireless Rogue Device Detection, Daniel Chege

Theses, Dissertations and Culminating Projects

Existing network detection techniques rely on SSIDs, network patterns or MAC addresses of genuine wireless devices to identify malicious attacks on the network. However, these device characteristics can be manipulated posing a security threat to information integrity, lowering detection accuracy, and weakening device protection. This research study focuses on empirical analysis to elaborate the relationship between received signal strength (RSSI) and distance; investigates methods to detect rogue devices and access points on Wi-Fi networks using network traffic analysis and fingerprint identification methods. In this paper, we conducted three experiments to evaluate the performance of RSSI and clock skews as features …

Detecting Bots Using A Hybrid Approach, Edmund Kofi Genfi

Theses, Dissertations and Culminating Projects

Artificial intelligence (AI) remains a crucial aspect for improving our modern lives but it also casts several social and ethical issues. One issue is of major concern, investigated in this research, is the amount of content users consume that is being generated by a form of AI known as bots (automated software programs). With the rise of social bots and the spread of fake news more research is required to understand how much content generated by bots is being consumed. This research investigates the amount of bot generated content relating to COVID-19. While research continues to uncover the extent to …

Fingerprint Classification Using Transfer Learning Technique, Aseel H. Aloweiwi

Theses, Dissertations and Culminating Projects

Fingerprints play a significant role in many sectors. Nowadays, fingerprints are used for identification purposes in criminal investigations. They are also used as an authentication method since they are considered more secure than passwords. Fingerprint sensors are already widely deployed in many devices, including mobile phones and smart locks. Criminals try to compromise biometric fingerprint systems by purposely altering their fingerprints or entering fake ones. Therefore, it is critical to design and develop a highly accurate fingerprint classification. However, some fingerprint datasets are small and not sufficient to train a neural network. Thus, transfer learning is utilized. A large Sokoto …

On-Focus : A Web-Based Platform For Planning, Organizing, And Managing Focus Groups, Nnamdi Chuka-Maduji

Theses, Dissertations and Culminating Projects

Focus groups are a research methodology that researchers use to get qualitative data about a subject matter or a product. Owing to the Covid outbreak in 2019 and the prevalence of group think in focus groups, a web-based platform called On-Focus was developed as a means for researchers to organize and manage focus groups online.

On-Focus was developed by following the recommended design approach for conducting focus groups found in literatures. With On-Focus, researchers can filter out participants that are not a fit for the focus group by asking questions that are filled by participants before they send a request …

Fast And Secure Friend Recommendation In Online Social Networks, Raiyan Hossain

Theses, Dissertations and Culminating Projects

Online Social Networks have completely transformed communication in the world of social networks. Participation in online social networks have been growing significantly and is expected to continue to grow in the upcoming years. As user participation in online social media is on the rise, so is the concern pertaining to user privacy and information security; users want to interact on social media without jeopardizing their privacy and personal information. Extensive research has been conducted in the area of developing privacy-preserving protocols to allow users to interact in a secure and privacy-preserving environment. One of the elements that social media have …

Recommender App Development For Essential Health Products : Covid And Beyond, Jessica Lourenco

Theses, Dissertations and Culminating Projects

The COVID-19 pandemic has affected all of our lives in many ways and as a result people have become more health conscious. Now more than ever it is critical to take cautious steps to prevent being infected and spreading the virus. It is important to be supplied with the right products that maintain us all safe and healthy. Although many stores have health related products, sometimes it is a hassle to find them and even to pick out the best ones. With that, the Health Essentials app was developed to facilitate the findings of health products. The app is solely …

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 …

A Web Application To Disseminate Repatriation And Travel Information About African Countries, Daniel Otuo-Acheampong

Theses, Dissertations and Culminating Projects

Africa is a continent with incredibly diversified cultures, landscapes, and people. Due its vastness, it can be difficult to assess accurate travel related information about African countries. The purpose of this project is to build a website that will serve as an African destination information insider. African countries are drawing people from all around the world, and this is evident in the formulation of initiatives to attract people to the continent during the past decade. Prime examples of these initiatives include Ghana’s Year of Return initiative and Nigeria’s door of return. This project, that entails the design and development of …

Assisting Humans In Human-Robot Co-Carry Tasks Using Robot-Trusting-Human Model, Corey Hannum

Theses, Dissertations and Culminating Projects

Robots are increasingly being employed for diverse applications where they must work and coexist with humans. The trust in human-robot collaboration (HRC) is a critical aspect of any shared task performance for both the human and the robot. The study of human-trusting-robot has been investigated by numerous researchers. However, robot-trusting-human, which is also a significant issue in HRC, is seldom explored in the field of robotics. In this paper we propose a novel trust-assist framework for human-robot co-carry tasks. This framework allows the robot to determine a trust level on the human co-carry partner. The calculations of this trust level …

Human-Robot Collaboration Using Commonsense Knowledge In Smart Manufacturing Contexts, Christopher Joseph Conti

Theses, Dissertations and Culminating Projects

Human-robot collaboration (HRC), where humans and robots work together on specific tasks, is a growing part of smart manufacturing that entails artificial intelligence (AI) techniques in manufacturing processes. Robots need to be able to dynamically understand their working environments and human partners both accurately and quickly, as inaccurate or slow predictions can be dangerous to humans and collaborative tasks. To handle challenging environments, robots need to utilize commonsense knowledge (CSK), which is everyday knowledge about fundamental concepts, such as how basic objects interact with each other, what their properties are, and how they are associated. Human beings utilize CSK regularly, …

Deep Learning For Electricity Forecasting Using Time Series Data, Hanan Abdullah Alshehri

Theses, Dissertations and Culminating Projects

The complexity and nonlinearities of the modern power grid render traditional physical modeling and mathematical computation unrealistic. AI and predictive machine learning techniques allow for accurate and efficient system modeling and analysis. Electricity consumption forecasting is highly valuable in energy management and sustainability research. Furthermore, accurate energy forecasting can be used to optimize energy allocation. This thesis introduces Deep Learning models including the Convolutional Neural Network (CNN), the Recurrent neural network (RNN), and Long Short-Term memory (LSTM). The Hourly Usage of Energy (HUE) dataset for buildings in British Columbia is used as an example for our investigation, as the dataset …

Small Business Owner App To Showcase Covid Prevention Policies And Reopening Guidelines, Christopher Duran

Theses, Dissertations and Culminating Projects

Almost a year after the emergence of the Coronavirus, the pandemic still negatively affects the world’s economy and quality of life. In the U.S., Covid-19 has shut down nearly 100,000 businesses.

The goal of this project is to develop an app that can assist business owners to accurately display their coronavirus prevention methods so that people can feel safe while using their services. This project will focus on how the business owner (Vendor) will be able to interact, utilize, and display important information for the customer (Patron) to use.

The vendor will be able to create an individual profile for …

Mcst : An App For Patron Awareness Of Covid-19 Safety Measures Instituted By Small Businesses, Jorge Torres

Theses, Dissertations and Culminating Projects

Small businesses across America are having restrictions placed upon them due to the COVID-19 pandemic. Those fortunate enough to remain open now face the challenge of trying to generate enough revenue to stay afloat. Small businesses, with their lack of funds, have resorted to listing their safety precautions on their front door to inform patrons. However, viewing these rules would require patrons to leave their homes. Additionally, there is no consistent set of rules being enforced by the government which is dangerous as some patrons may feel that stricter procedures be in place. These inconsistencies and lack of information can …

Dfl-Opt : A Daily Fantasy Lineup Optimizer, Francis Aurori

Theses, Dissertations and Culminating Projects

[Background] Daily fantasy sports (DFS) are a variety of fantasy sports where contests take place in a matter of days or hours rather than over a whole season. A disparity exists between skilled professionals and casual participants in the creation of line-ups (i.e. teams) w.r.t their chances of winning in these contests. The purpose of the current project was to create a user-friendly, open source platform (named DFL-Opt) for participants of all skill levels to utilize in the creation of DFS line-ups. In addition, efficacy of the DFL-Opt platform was determined by playing the lineups generated by the DFL-Opt tool …

A Privacy-Aware Framework For Friend Recommendations In Online Social Networks, Mona Fahad Alkanhal

Theses, Dissertations and Culminating Projects

Online social networks (OSN), such as Facebook, Twitter, and LinkedIn, have revolutionized the way how people share information and stay connected with family and friends. Along this direction, user’s privacy has been a significant concern to all users in the social networks. In this thesis, we propose a privacyaware framework that allows users to outsource their encrypted profile data to a cloud environment. In order to achieve better security and efficiency, our framework utilizes a hybrid approach that consists of Paillier’s encryption scheme and AES. Furthermore, we develop a privacy-aware friend recommendation protocol that recommends new friends to social network …

Data Mining And Predictive Policing, Chanté L. Stewart-Wallace

Theses, Dissertations and Culminating Projects

This paper focuses on the operation and utilization of predictive policing software that generates spatial and temporal hotspots. There is a literature review that evaluates previous work surrounding the topics branched from predictive policing. It dissects two different crime datasets for San Francisco, California and Chicago, Illinois. Provided, is an in depth comparison between the datasets using both statistical analysis and graphing tools. Then, it shows the application of the Apriori algorithm to re-enforce the formation of possible hotspots pointed out in a actual predictive policing software. To further the analysis, targeted demographics of the study were evaluated to create …

Commonsense Knowledge In Sentiment Analysis Of Ordinance Reactions For Smart Governance, Manish Puri

Theses, Dissertations and Culminating Projects

Smart Governance is an emerging research area which has attracted scientific as well as policy interests, and aims to improve collaboration between government and citizens, as well as other stakeholders. Our project aims to enable lawmakers to incorporate data driven decision making in enacting ordinances. Our first objective is to create a mechanism for mapping ordinances (local laws) and tweets to Smart City Characteristics (SCC). The use of SCC has allowed us to create a mapping between a huge number of ordinances and tweets, and the use of Commonsense Knowledge (CSK) has allowed us to utilize human judgment in mapping. …

A Privacy-Preserving Framework For Collaborative Association Rule Mining In Cloud, Salha Albehairi

Theses, Dissertations and Culminating Projects

Collaborative Data Mining facilitates multiple organizations to integrate their datasets and extract useful knowledge from their joint datasets for mutual benefits. The knowledge extracted in this manner is found to be superior to the knowledge extracted locally from a single organization’s dataset. With the rapid development of outsourcing, there is a growing interest for organizations to outsource their data mining tasks to a cloud environment to effectively address their economic and performance demands. However, due to privacy concerns and stringent compliance regulations, organizations do not want to share their private datasets neither with the cloud nor with other participating organizations. …