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Full-Text Articles in Computer Sciences
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 …
Modelling Customers Credit Card Behaviour Using Bidirectional Lstm Neural Networks, Maher Ala’Raj, Maysam F. Abbod, Munir Majdalawieh
Modelling Customers Credit Card Behaviour Using Bidirectional Lstm Neural Networks, Maher Ala’Raj, Maysam F. Abbod, Munir Majdalawieh
All Works
With the rapid growth of consumer credit and the huge amount of financial data developing effective credit scoring models is very crucial. Researchers have developed complex credit scoring models using statistical and artificial intelligence (AI) techniques to help banks and financial institutions to support their financial decisions. Neural networks are considered as a mostly wide used technique in finance and business applications. Thus, the main aim of this paper is to help bank management in scoring credit card clients using machine learning by modelling and predicting the consumer behaviour with respect to two aspects: the probability of single and consecutive …
Can We Classify Cashless Payment Solution Implementations At The Country Level?, Dennis Ng, Robert J. Kauffman, Paul Robert Griffin
Can We Classify Cashless Payment Solution Implementations At The Country Level?, Dennis Ng, Robert J. Kauffman, Paul Robert Griffin
Research Collection School Of Computing and Information Systems
This research commentary proposes a 3-D implementation classification framework to assist service providers and business leaders in understanding the kinds of contexts in which more or less successful cashless payment solutions are observed at point-of-sale (PoS) settings. Three constructs characterize the framework: the digitalization of the local implementation environment; the relative novelty of a given payment technology solution in a country at a specific point in time; and the development status of the country’s national infrastructure. The framework is motivated by a need to support cross-country research in this domain. We analyze eight country mini-cases based on an eight-facet (2 …
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
An Investigation Of Decision Analytic Methodologies For Stress Identification, Yong Deng, Chao-Hsien Chu, Huayou Si, Qixun Zhang, Zhonghai Wu
Research Collection School Of Computing and Information Systems
In modern society, more and more people are suffering from some type of stress. Monitoring and timely detecting of stress level will be very valuable for the person to take counter measures. In this paper, we investigate the use of decision analytics methodologies to detect stress. We present a new feature selection method based on the principal component analysis (PCA), compare three feature selection methods, and evaluate five information fusion methods for stress detection. A driving stress data set created by the MIT Media lab is used to evaluate the relative performance of these methods. Our study show that the …