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Full-Text Articles in Physical Sciences and Mathematics
A Review Of Hybrid Cyber Threats Modelling And Detection Using Artificial Intelligence In Iiot, Yifan Liu, Shancang Li, Xinheng Wang, Li Xu
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 …
Machine-Learning-Based Vulnerability Detection And Classification In Internet Of Things Device Security, Sarah Bin Hulayyil, Shancang Li, Li Da Xu
Machine-Learning-Based Vulnerability Detection And Classification In Internet Of Things Device Security, Sarah Bin Hulayyil, Shancang Li, Li Da Xu
Information Technology & Decision Sciences Faculty Publications
Detecting cyber security vulnerabilities in the Internet of Things (IoT) devices before they are exploited is increasingly challenging and is one of the key technologies to protect IoT devices from cyber attacks. This work conducts a comprehensive survey to investigate the methods and tools used in vulnerability detection in IoT environments utilizing machine learning techniques on various datasets, i.e., IoT23. During this study, the common potential vulnerabilities of IoT architectures are analyzed on each layer and the machine learning workflow is described for detecting IoT vulnerabilities. A vulnerability detection and mitigation framework was proposed for machine learning-based vulnerability detection in …
Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh
Why Do Family Members Reject Ai In Health Care? Competing Effects Of Emotions, Eun Hee Park, Karl Werder, Lan Cao, Balasubramaniam Ramesh
Information Technology & Decision Sciences Faculty Publications
Artificial intelligence (AI) enables continuous monitoring of patients’ health, thus improving the quality of their health care. However, prior studies suggest that individuals resist such innovative technology. In contrast to prior studies that investigate individuals’ decisions for themselves, we focus on family members’ rejection of AI monitoring, as family members play a significant role in health care decisions. Our research investigates competing effects of emotions toward the rejection of AI monitoring for health care. Based on two scenario-based experiments, our study reveals that emotions play a decisive role in family members’ decision making on behalf of their parents. We find …