Digital Humanities: Using Computational Methods On Literature To Understand Human-Water Relations,
2024
William & Mary
Digital Humanities: Using Computational Methods On Literature To Understand Human-Water Relations, Ariel Yang
Cybersecurity Undergraduate Research Showcase
By using computational techniques to analyze literature, deeper insights can be gained into human-water relationships across different historical and cultural contexts. Natural Language Processing (NLP) and other data science methods can explore applications of traditional ecological knowledge (TEK) and underlying emotions or beliefs in literature to help understand sustainability. Protecting this sensitive cultural data through ethical applications can further secure future implementations of policies, urban planning, and environmental relationships.
Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures,
2024
Old Dominion University
Security Vulnerabilities In Mobile Operating Systems Used In Iot Devices: An Examination Of Current Challenges And Countermeasures, Isain Cortes Jr.
Cybersecurity Undergraduate Research Showcase
No abstract provided.
Medilink: A Secure Blockchain Framework For Multi-Institutional Healthcare,
2024
The University of Texas Rio Grande Valley
Medilink: A Secure Blockchain Framework For Multi-Institutional Healthcare, Jorge Castillo, Qian Chen
Informatics and Engineering Systems Faculty Publications
The use of Electronic Medical Records (EMRs) in the healthcare industry has proven to be critical for storing highly sensitive information. Disseminating and protecting healthcare data poses major challenges for the current healthcare information system. Blockchain technology provides solutions to these challenges with its inherited properties, such as decentralization, immutability, and transparency. This provides a unique opportunity to improve data sharing among stakeholders. We propose MediLink, a blockchain-based framework for secure collaborative medical storage. MediLink is designed to (1) protect EMR data from cyber attacks, (2) share healthcare information of patients with different stakeholders, and (3) enable the Internet of …
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread,
2024
William & Mary
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread, James Johnson
Cybersecurity Undergraduate Research Showcase
Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself …
Integrating Humanities Into Cybersecurity Education: Enhancing Ethical, Historical, And Sociopolitical Understanding In Technical Training,
2024
The College of Staten Island, CUNY
Integrating Humanities Into Cybersecurity Education: Enhancing Ethical, Historical, And Sociopolitical Understanding In Technical Training, Joseph Frusci
Journal of Cybersecurity Education, Research and Practice
The increasing complexity of cybersecurity challenges necessitates a holistic educational approach that integrates both technical skills and humanistic perspectives. This article examines the importance of infusing humanities disciplines such as history, ethics, political science, sociology, law, and anthropology—into cybersecurity education. Through a pilot course developed for Staten Island Technical High School, aligned with the New York State K-12 Computer Science and Digital Fluency Standards, students were introduced to an interdisciplinary curriculum that combined technical cybersecurity training with historical analysis, ethical reasoning, and sociopolitical context. The results of pre- and post-course assessments demonstrated significant improvements in critical thinking, ethical decision-making, and …
Beyond Human-Centric Models In Cybersecurity Education: A Pilot Posthuman Analysis Of The Nice Workforce Framework For Cybersecurity,
2024
University of Arizona
Beyond Human-Centric Models In Cybersecurity Education: A Pilot Posthuman Analysis Of The Nice Workforce Framework For Cybersecurity, Ryan Straight
Journal of Cybersecurity Education, Research and Practice
This study applies a posthuman lens to the National Initiative for Cybersecurity Education (NICE) Workforce Framework, examining two key Work Roles in cybersecurity education. Employing a novel posthuman coding scheme, the associated Tasks, Knowledge, and Skills (TKS) statements were analyzed. Findings reveal significant posthuman elements within the framework while identifying opportunities for further integration. The analysis demonstrates a strong presence of human-technology entanglement and adaptive learning concepts, yet highlights areas where the framework could emphasize system complexity and interconnectedness. This research contributes to ongoing discussions on cybersecurity education in complex technological landscapes, proposing a theoretical framework for integrating posthuman concepts …
Phishing Emails: An Evolving Cyberattack,
2024
Christopher Newport University
Phishing Emails: An Evolving Cyberattack, Brooke Waltz
Cybersecurity Undergraduate Research Showcase
This paper describes the history of phishing attacks and how they turned into cyberattacks, focusing on companies. Over the course of 34 years, phishing has been evolving at an alarming rate, especially with AI now coming into play. As phishing attacks have become more prominent towards companies, there has been an increase in financial loss and data breaches, resulting in a loss of trust in companies. With this loss, companies are trying to find solutions to this problem. Some notable attacks were the RSA breach in 2011, the Texas Energy Company in 2014, and the ILOVEYOU virus in 2000. They …
A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models,
2024
United Arab Emirates University
A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models, Ashika Sameem Abdul Rasheed
Thesis/ Dissertation Defenses
This thesis examines the use of Large Language Models (LLMs) in education, with a focus on improving performance and implementing strong security measures. The research has two main goals, namely, the development of an effective lecture summarization technique using LLMs and identifying and addressing security vulnerabilities in LLM applications according to OWASP (Open Web Application Security Project) guidelines. For the former goal, we have proposed an effective framework for fine-tuning LLMs using real lecture datasets and compared the performance of different LLMs. For the latter goal, we conducted a thorough review of the application dataflow of the proposed framework and …
Inferring Tlb Configuration With Performance Tools,
2024
Air Force Institute of Technology
Inferring Tlb Configuration With Performance Tools, Cristian Agredo, Tor J. Langehaug, Scott R. Graham
Faculty Publications
Modern computing systems are primarily designed for maximum performance, which inadvertently introduces vulnerabilities at the micro-architecture level. While cache side-channel analysis has received significant attention, other Central Processing Units (CPUs) components like the Translation Lookaside Buffer (TLB) can also be exploited to leak sensitive information. This paper focuses on the TLB, a micro-architecture component that is vulnerable to side-channel attacks. Despite the coarse granularity at the page level, advancements in tools and techniques have made TLB information leakage feasible. The primary goal of this study is not to demonstrate the potential for information leakage from the TLB but to establish …
Developing A Framework For Digital Twin Data Quality And Security Controls,
2024
United Arab Emirates University
Developing A Framework For Digital Twin Data Quality And Security Controls, Ahmad Abdelbaset Hassan
Thesis/ Dissertation Defenses
This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin standards and policies that is going to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust standards to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed …
Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence,
2024
United Arab Emirates University
Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous
Thesis/ Dissertation Defenses
With the increase in popularity of online communities, such as social media platforms, online games, and chatroom servers, there is a need to improve chat and content moderation. Platforms have reported an increase in the prevalence of toxic behavior and hate speech. Meanwhile, moderators are reporting difficulties in keeping up with the amount of data to check as well and the type of content they are exposed to, which further harms their own mental health. The main objective of this work is to address the challenges that exist within online communities with the rising prevalence of hate speech. Additionally, some …
An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme For Internet Of Things,
2024
Edith Cowan University
An Efficient Pairing-Free Ciphertext-Policy Attribute-Based Encryption Scheme For Internet Of Things, Chong Guo, Bei Gong, Muhammad Waqas, Hisham Alasmary, Shanshan Tu, Sheng Chen
Research outputs 2022 to 2026
The Internet of Things (IoT) is a heterogeneous network composed of numerous dynamically connected devices. While it brings convenience, the IoT also faces serious challenges in data security. Ciphertext-policy attribute-based encryption (CP-ABE) is a promising cryptography method that supports fine-grained access control, offering a solution to the IoT’s security issues. However, existing CP-ABE schemes are inefficient and unsuitable for IoT devices with limited computing resources. To address this problem, this paper proposes an efficient pairing-free CP-ABE scheme for the IoT. The scheme is based on lightweight elliptic curve scalar multiplication and supports multi-authority and verifiable outsourced decryption. The proposed scheme …
Efficient Multiplicative-To-Additive Function From Joye-Libert Cryptosystem And Its Application To Threshold Ecdsa,
2024
Singapore Management University
Efficient Multiplicative-To-Additive Function From Joye-Libert Cryptosystem And Its Application To Threshold Ecdsa, Haiyang Xue, Ho Man Au, Mengling Liu, Yin Kwan Chan, Handong Cui, Xiang Xie, Hon Tsz Yuen, Chengru Zhang
Research Collection School Of Computing and Information Systems
Threshold ECDSA receives interest lately due to its widespread adoption in blockchain applications. A common building block of all leading constructions involves a secure conversion of multiplicative shares into additive ones, which is called the multiplicative-to-additive (MtA) function. MtA dominates the overall complexity of all existing threshold ECDSA constructions. Specifically, O(n2) invocations of MtA are required in the case of n active signers. Hence, improvement of MtA leads directly to significant improvements for all state-of-the-art threshold ECDSA schemes.In this paper, we design a novel MtA by revisiting the Joye-Libert (JL) cryptosystem. Specifically, we revisit JL encryption and propose a JL-based …
Lr-Auth: Towards Practical Implementation Of Implicit User Authentication On Earbuds,
2024
Singapore Management University
Lr-Auth: Towards Practical Implementation Of Implicit User Authentication On Earbuds, Changshuo Hu, Xiao Ma, Xinger Huang, Yiran Shen, Dong Ma
Research Collection School Of Computing and Information Systems
The increasing use of earbuds in applications like immersive entertainment and health monitoring necessitates effective implicit user authentication systems to preserve the privacy of sensitive data and provide personalized experiences. Existing approaches, which leverage physiological cues (e.g., jawbone structure) and behavioral cues (e.g., gait), face challenges such as limited usability, high delay and energy overhead, and significant computational demands, rendering them impractical for resource-constrained earbuds. To address these issues, we present LR-Auth, a lightweight, user-friendly implicit authentication system designed for various earbud usage scenarios. LR-Auth utilizes the modulation of sound frequencies by the user's unique occluded ear canal, generating user-specific …
Adversarial Learning For Coordinate Regression Through K-Layer Penetrating Representation,
2024
Fuzhou University
Adversarial Learning For Coordinate Regression Through K-Layer Penetrating Representation, Mengxi Jiang, Yulei Sui, Yunqi Lei, Xiaofei Xie, Cuihua Li, Yang Liu, Ivor W. Tsang
Research Collection School Of Computing and Information Systems
Adversarial attack is a crucial step when evaluating the reliability and robustness of deep neural networks (DNNs) models. Most existing attack approaches apply an end-to-end gradient update strategy to generate adversarial examples for a classification or regression problem. However, few of them consider the non-differentiable DNN models (e.g., coordinate regression model) that prevent end-to-end backpropagation resulting in the failure of gradient calculation. In this paper, we present a new adversarial example generation approach for both untargeted and targeted attacks on coordinate regression models with non-differentiable operations. The novelty of our approach lies in a k-layer penetrating representation, on which we …
Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective,
2024
Singapore Management University
Badfl: Backdoor Attack Defense In Federated Learning From Local Model Perspective, Haiyan Zhang, Xinghua Li, Mengfan Xu, Ximeng Liu, Tong Wu, Jian Weng, Robert H. Deng
Research Collection School Of Computing and Information Systems
There is substantial attention to federated learning with its ability to train a powerful global model collaboratively while protecting data privacy. Despite its many advantages, federated learning is vulnerable to backdoor attacks, where an adversary injects malicious weights into the global model, making the global model's targeted predictions incorrect. Existing defenses based on identifying and eliminating malicious weights ignore the similarity variation of the local weights during iterations in the malicious model detection and the presence of benign weights in the malicious model during the malicious local weight elimination, resulting in a poor defense and a degradation of global model …
Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence,
2024
United Arab Emirates University
Tackling Toxicity And Harassment In Online Environments Through The Use Of Artificial Intelligence, Heba Saleous
Dissertations
With the increase in popularity of online communities, such as social media platforms, online games, and chatroom servers, there is a need to improve chat and content moderation. Platforms have reported an increase in the prevalence of toxic behavior and hate speech. Meanwhile, moderators are reporting difficulties in keeping up with the amount of data to check as well and the type of content they are exposed to, which further harms their own mental health. The main objective of this work is to address the challenges that exist within online communities with the rising prevalence of hate speech. Additionally, some …
A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models,
2024
United Arab Emirates University
A Secure And Effective Framework For Key Concept Mining From Educational Content Using Large Language Models, Ashika Sameem Abdul Rasheed
Theses
This thesis examines the use of Large Language Models (LLMs) in education, with a focus on improving performance and implementing strong security measures. The research has two main goals, namely, the development of an effective lecture summarization technique using LLMs and identifying and addressing security vulnerabilities in LLM applications according to OWASP (Open Web Application Security Project) guidelines. For the former goal, we have proposed an effective framework for fine-tuning LLMs using real lecture datasets and compared the performance of different LLMs. For the latter goal, we conducted a thorough review of the application dataflow of the proposed framework and …
Developing Policies For Digital Twin Data Quality And Security Controls,
2024
United Arab Emirates University
Developing Policies For Digital Twin Data Quality And Security Controls, Ahmad Abdelbaset Hassan
Theses
This thesis is concerned with the data quality and security of the digital twin and how it is going to impact its adoption, trustworthiness, and potential for real-world applications. By addressing the potential vulnerabilities and ensuring the integrity of data, this research aims to contribute to the development of robust and trustworthy digital twin policies that to complement the existing international standards across different domains. Moreover, it underscores the important need to establish robust policies to ensure the successful and secure deployment of digital twins across industries. Previous research, while valuable, may not have fully addressed the critical interplay between …
Maritime Behaviour Anomaly Detection With Seasonal Context,
2024
Edith Cowan University
Maritime Behaviour Anomaly Detection With Seasonal Context, Travis Rybicki, Martin Masek, Chiou Peng Lam
Research outputs 2022 to 2026
Monitoring maritime traffic has become an important task for ensuring the safety of vessels, as well as the goods, and persons that they may be transporting. An active area of research is the modelling of expected normal vessel behaviour so as to detect subsequent anomalies in new data. Anomalies indicate that a vessel is not behaving in an expected manner and their detection can be flagged for further investigation to identify whether the vessel needs assistance or intervention. An important factor for some vessels in determining normal behaviour is seasonal context. However, current approaches typically do not incorporate seasonality into …
