Information Security Commons^™

Building New Paradigm Of Digital Intelligence Security For New Development Pattern, Xiaoguang Yang, Yang Wu, Xingwei Zhang, Xiaolong Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

After the 20th National Congress of the Communist Party of China, China has entered a new era of development. Simultaneously, the rapid advancement and extensive application of artificial intelligent technologies have activated a new wave of economic potential and brought about new security challenges to socioeconomic development. This study firstly analyzes the characteristics of the new development pattern in global contexts, and examines the risks and challenges of digital intelligence security (DIS) under the new pattern, encompassing technological security and personal security at the micro-level, as well as economic security, social security, and cultural security at the macro-level. Based on …

Towards Assessing Cybersecurity Posture Of Manufacturing Companies: Review And Recommendations, John Del Vecchio, Yair Levy, Ling Wang, Ajoy Kumar

KSU Proceedings on Cybersecurity Education, Research and Practice

With the continued changes in the way businesses work, cyber-attack targets are in a constant state of flux between organizations, individuals, as well as various aspects of the supply chain of interconnected goods and services. As one of the 16 critical infrastructure sectors, the manufacturing sector is known for complex integrated Information Systems (ISs) that are incorporated heavily into production operations. Many of these ISs are procured and supported by third parties, also referred to as interconnected entities in the supply chain. Disruptions to manufacturing companies would not only have significant financial losses but would also have economic and safety …

Quantum Computing: Computing Of The Future Made Reality, Janelle Mathis

KSU Proceedings on Cybersecurity Education, Research and Practice

Abstract—Quantum computing is an emerging new area focused on technology consisting of quantum theory aspects such as electrons, sub-atomic particles, and other materials engineered using quantum mechanics. Through quantum mechanics, these computers can solve problems that classical computers deem too complex. Today the closest computing technology compared to quantum computers are supercomputers, but similarly to classical computers, supercomputers also have faults. With supercomputers, when a problem is deemed too complex, it is due to the classical machinery components within the computer, thus causing a halt in solving the task or problem. In contrast, these problems could be solved with a …

Rfid Key Fobs In Vehicles: Unmasking Vulnerabilities & Strengthening Security, Devon Magda, Bryson R. Payne

KSU Proceedings on Cybersecurity Education, Research and Practice

No abstract provided.

The Impact Of Individual Techno-Characteristics On Information Privacy Concerns In The Diffusion Of Mobile Contact Tracing, Jiesen Lin, Dapeng Liu, Lemuria Carter

KSU Proceedings on Cybersecurity Education, Research and Practice

In the wake of the global health crisis, mobile contact tracing applications have emerged as important tools in managing disease spread. However, their effectiveness heavily relies on mass adoption, significantly influenced by the public's information privacy concerns. To date, systematic examination of how these privacy concerns relate to the innovation adopter categories in mobile contact tracing remains sparse. Furthermore, the influence of individual techno-characteristics on these concerns is to be explored. This research seeks to fill these gaps. Drawing on the diffusion of innovation theory, we examine the impact of the key techno-characteristics—adopter category, propensity for identification misrepresentation, and exposure …

Exploring Information Privacy Concerns During The Covid-19 Pandemic: A Juxtaposition Of Three Models, Dapeng Liu, Lemuria Carter, Jiesen Lin

KSU Proceedings on Cybersecurity Education, Research and Practice

Government agencies across the globe utilize mobile applications to interact with constituents. In response to the global pandemic, several nations have employed contact tracing services to manage the spread of COVID-19. Extent literature includes various models that explore information privacy. Several researchers have highlighted the need to compare the effectiveness of diverse information privacy models. To fill this gap, we explore the impact of information privacy concerns on citizens’ willingness to download a federal contact tracing app. In particular, we compare three types of prevalent information privacy concerns: global information privacy concerns (GIPC), concern for information privacy (CFIP), and internet …

How Increased Ransomware Attacks Have Impacted Hospitals In The United States, Mackenzie Dotson

Theses, Dissertations and Capstones

Introduction: The healthcare industry, particularly hospitals, have fallen prey to the alarming rise of ransomware attacks. In recent years, highly sophisticated cybergroups, armed with substantial funds and advanced technology, have intensified their focus on hospitals. Despite the advice against it, most hospitals have paid the ransom in order to regain access to their electronic systems and patient data, underlining the severity of these attacks.

Purpose of the Study: The purpose of this research was to evaluate the effects of ransomware attacks on hospitals in the US to determine if the patients were at risk due to hackers withholding patient information …

A Review Of Hybrid Cyber Threats Modelling And Detection Using Artificial Intelligence In Iiot, Yifan Liu, Shancang Li, Xinheng Wang, Li Xu

Information Technology & Decision Sciences Faculty Publications

The Industrial Internet of Things (IIoT) has brought numerous benefits, such as improved efficiency, smart analytics, and increased automation. However, it also exposes connected devices, users, applications, and data generated to cyber security threats that need to be addressed. This work investigates hybrid cyber threats (HCTs), which are now working on an entirely new level with the increasingly adopted IIoT. This work focuses on emerging methods to model, detect, and defend against hybrid cyber attacks using machine learning (ML) techniques. Specifically, a novel ML-based HCT modelling and analysis framework was proposed, in which regularisation and Random Forest …

It Is Not Only About Having Good Attitudes: Factor Exploration Of The Attitudes Toward Security Recommendations, Miguel A. Toro-Jarrin, Pilar Pazos, Miguel A. Padilla

Engineering Management & Systems Engineering Faculty Publications

Numerous factors determine information security-related actions (IS-actions) in the workplace. Attitudes toward following security rules and recommendations and attitudes toward specific IS actions determine intentions associated with those actions. IS research has examined the role of the instrumental aspect of attitudes. However, authors argue that attitudes toward a behavioral object are a multidimensional construct. We examined the dimensionality of attitudes toward security recommendations, hypothesized its multidimensional nature, and developed a new scale [attitudes toward security recommendations (ASR scale)]. The results indicated the multidimensional nature of attitudes toward security recommendations supporting our hypothesis. The results revealed two dimensions corresponding to the …

A Comprehensive And Comparative Examination Of Healthcare Data Breaches: Assessing Security, Privacy, And Performance, Mohammed Al Kinoon

Graduate Thesis and Dissertation 2023-2024

The healthcare sector is pivotal, offering life-saving services and enhancing well-being and community life quality, especially with the transition from paper-based to digital electronic health records (EHR). While improving efficiency and patient safety, this digital shift has also made healthcare a prime target for cybercriminals. The sector's sensitive data, including personal identification information, treatment records, and SSNs, are valuable for illegal financial gains. The resultant data breaches, increased by interconnected systems, cyber threats, and insider vulnerabilities, present ongoing and complex challenges. In this dissertation, we tackle a multi-faceted examination of these challenges. We conducted a detailed analysis of healthcare data …

Understanding Social Dynamics In Toxic Conversations And Public Health Intervention Acceptance On Social Media, Ana Aleksandric

Computer Science and Engineering Dissertations - Archive

Social media is now central to daily life, offering users a space to share content and opinions. However, these platforms also facilitate the spread of hate speech and misinformation, which can negatively impact public health. This dissertation develops methodologies to analyze social media data for insights that could inform health interventions. The research first examines user responses to toxic content, focusing on behavioral and emotional reactions, as well as group dynamics and bystander effects in toxic interactions. Another key focus is public opinion toward health interventions, particularly COVID-19 vaccination, using geolocated posts and analyzing factors such as race, ethnicity, and …

Tapped In: The Rise Of Mobile Malware, Chrystofuer Davenport

Cybersecurity Undergraduate Research Showcase

As the world of technology continues to evolve and become more advanced with our life, so do the dangers and threats that are determined to hinder that development. Malware continues to be a danger to internet surfers or people with access to technology. At first it was an issue that existed only with computers but since the evolution of smartphones in the early twenty-first century, mobile devices have been a target for multiple malware viruses. It’s important to be aware of what different viruses are capable of doing and how to avoid them when they are encountered. Even though computers …

Sscm: A Secured Approach To Supply Chain Management Using Blowfish Optimization, Shitharth Selvarajan, Hariprasath Manoharan, Alaa O. Khadidos, Achyut Shankar, Adil O. Khadidos, Wattana Viriyasitavat, Li Da Xu

Information Technology & Decision Sciences Faculty Publications

This study examines the importance of enterprise information systems that link several corporate organisations to share information about diverse products under high security settings. The primary goal of the proposed strategy is to create a direct link between product demand and production to minimise the impact of rising costs. The research motive to make a connection cannot be resolved without suitable data that shows both quantity and quality in each organisation unit. The suggested method is designed to deliver accurate data to authorised end users while preventing any data exposure to unauthorised users. Security cryptographic keys are utilised to create …

Content Moderation On Social Media: Social And Computational Standards And Implications, Mohit Singhal

Computer Science and Engineering Dissertations - Archive

Social media has become a powerful tool that reflects human communication's best and worst aspects. They allow individuals to freely express opinions, communicate with others, and learn about new stories. On the other hand, they have become fertile grounds for several forms of abuse, harassment, and the dissemination of misinformation. Social media platforms have established and employed content moderation to counteract the spread of abuse and misinformation.

Some critical challenges hinder the understanding of the social media content moderation ecosystem. This dissertation investigates various aspects of content moderation, including their coverage, fairness, and effectiveness. Firstly, it investigates how, in practice, …

A Prototype Application For The Measurement Of Data Breach Event Intensity, James Palazzolo

Master's Theses and Doctoral Dissertations

The data breach phenomenon is not new. People have valued information, its protection, and its security for centuries. A data breach is the loss of control over one’s information. In contemporary society (circa 2024), a data breach can occur in several ways: through accidental disclosure, negligence, or malicious action. Likewise, the study of the data breach phenomenon is not new. As with other studies, this research effort seeks to expand the current body of knowledge concerning data breaches. However, unlike previous research, we adopt a novel approach to further our understanding of the phenomenon. By employing topological and phenomenological thinking, …

Privacy And Security Of The Windows Registry, Edward L. Amoruso

Graduate Thesis and Dissertation 2023-2024

The Windows registry serves as a valuable resource for both digital forensics experts and security researchers. This information is invaluable for reconstructing a user's activity timeline, aiding forensic investigations, and revealing other sensitive information. Furthermore, this data abundance in the Windows registry can be effortlessly tapped into and compiled to form a comprehensive digital profile of the user. Within this dissertation, we've developed specialized applications to streamline the retrieval and presentation of user activities, culminating in the creation of their digital profile. The first application, named "SeeShells," using the Windows registry shellbags, offers investigators an accessible tool for scrutinizing and …

Student Attitudes And Intentions To Use Continuous Authentication Methods Applied To Mitigate Impersonation Attacks During E-Assessments, Andrea E. Green

CCAC Theses and Dissertations

No solution can ultimately eliminate cheating in online courses. However, universities reserve funding for authentication systems to minimize the threat of cheating in online courses. Most higher education institutions use a combination of authentication methods to secure systems against impersonation attacks during online examinations. Authentication technologies ensure that an online course is protected from impersonation attacks. However, it is important that authentication methods secure systems against impersonation attacks with minimal disruption during an examination. Authentication methods applied to secure e-assessments against impersonation attacks may impact a student’s attitude and intentions to use the e-examination system.

In this regard, the research …

Federated Learning: Overview, Strategies, Applications, Tools And Future Directions, Betul Yurdem, Murat Kuzlu, Mehmet Kemal Gullu, Maliha Tabassum

Engineering Technology Faculty Publications

Federated learning (FL) is a distributed machine learning process, which allows multiple nodes to work together to train a shared model without exchanging raw data. It offers several key advantages, such as data privacy, security, efficiency, and scalability, by keeping data local and only exchanging model updates through the communication network. This review paper provides a comprehensive overview of federated learning, including its principles, strategies, applications, and tools along with opportunities, challenges, and future research directions. The findings of this paper emphasize that federated learning strategies can significantly help overcome privacy and confidentiality concerns, particularly for high-risk applications.

Enhancing Iot Security: Optimizing Anomaly Detection Through Machine Learning, Maria Balega, Waleed Farag, Xin-Wen Wu, Soundarararjan Ezekiel, Zaryn Good

Computer Science Articles

As the Internet of Things (IoT) continues to evolve, securing IoT networks and devices remains a continuing challenge. Anomaly detection is a crucial procedure in protecting the IoT. A promising way to perform anomaly detection in the IoT is through the use of machine learning (ML) algorithms. There is a lack of studies in the literature identifying optimal (with regard to both effectiveness and efficiency) anomaly detection models for the IoT. To fill the gap, this work thoroughly investigated the effectiveness and efficiency of IoT anomaly detection enabled by several representative machine learning models, namely Extreme Gradient Boosting (XGBoost), Support …

Predicting Viral Rumors And Vulnerable Users With Graph-Based Neural Multi-Task Learning For Infodemic Surveillance, Xuan Zhang, Wei Gao

Research Collection School Of Computing and Information Systems

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such misinformation. This proactive approach allows for timely preventive measures to be taken, mitigating the negative impact of false information on society. We propose a novel approach to predict viral rumors and vulnerable users using a unified graph neural network model. We pre-train network-based user embeddings and leverage a cross-attention mechanism between users and posts, together with a community-enhanced vulnerability propagation (CVP) …