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Doctoral Degrees (Information Systems and Technology)

Permanent URI for this collectionhttps://hdl.handle.net/10413/6926

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Browsing Doctoral Degrees (Information Systems and Technology) by SDG "SDG3"

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    Assessing the implementation of electronic consultation in the Ghanaian health sector.
    (2023) Nketia, Mark Ofori.; Maharaj, Manoj Sewak.
    The Covid-19 pandemic sparked the buzz word “e-consultation” because people preferred having medical attention remotely. The researcher carried out this study with the aim to help improve access to healthcare by identifying the key issues in the adoption and use of e-consultation in the Ghanaian Health Sector. The study evaluates how e-consultation systems influence the delivery of health care services in hospitals, assesses the attitudes of clinicians and patients towards e-consultation systems and provides a framework to enhance its usage. To assess the implementation of successful e-consultation, the researcher developed a conceptual model that bridged the Delone & Mclean’s IS success model, and Rogers’ Diffusion of Innovation Theory to form a suitable model for the study. The research utilized a sequential exploratory method, combining qualitative and quantitative methods to gain an in-depth understanding of the dynamics and challenges associated with e-consultation in the specific context of Ghana. The study found that the implementation of e-consultation is integrated in the internal hospital management system of very few hospitals. Hence most clinicians resort to using e-consultation informally with the help of WhatsApp video, Zoom, phone calls and other open source platforms. Also, it was found that the attitudes of clinicians and patients towards e-consultation implementation is influenced by various factors that range from system quality, information quality, ease of use, connectivity, and education. Besides, the growing concern of privacy and data security issues shows that healthcare providers should strengthen the development of e-consultation information systems. It transpired that the Ministry of Health does not have a suitable policy on software standards for e-consultation. The poor regulatory framework is a major factor contributing to resistance to the use of e-consultation. The rotated factor matrix extracted using the Principal Axis Factoring shows a high level of correlation and consistency among various factors under study. Attitude came first followed by Regulatory framework, acceptance and diffusion. The study, therefore, proposed a model for e-consultation implementation which would help regularize the implementation of e-consultation as well as enhancing the rate of diffusion of e-consultation, its adoption and usage by hospitals and the public.
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    The design and development of an AI based digital forensic protocol for first responders.
    (2024) Kumar, Deepak.; Subramaniam, Prabhakar Rontala.
    In today's society, access to computers and the internet has become indispensable, offering a myriad of opportunities such as online shopping, trading, banking, communication, and social media interaction. However, along with the increasing usage of the internet, there is a corresponding rise in cybercrimes, posing constant threats to organizations. Recent years have witnessed a significant surge in cyber incidents and breaches, exacerbated by emerging technologies like the Fourth Industrial Revolution (4IR) and Artificial Intelligence (AI), as well as the availability of tools such as Crimeware-as-a-Service (CaaS), anonymous technologies like Tor, and the utilization of the Darknet. In response to these challenges, cyber forensic experts and digital investigators must possess the necessary skills and expertise to effectively investigate cybercrimes, analyse electronic evidence found on digital devices, and present findings in a legally acceptable manner. To stay ahead of cybercriminals, digital forensic investigators and first responders must leverage AI and cutting-edge technologies of the 4IR era. This study addresses the evolving cybersecurity landscape by designing an AI-based digital forensic protocol tailored for first responders. Employing a design science research (DSR) methodology, the study develops a novel investigation protocol utilising AI prediction modelling. Additionally, it explores various AI models to create an efficient framework for integrating Machine Learning (ML) and predictive modelling in cybercrime data analysis of a cloud-based dataset. The design and development of Intelligent Digital Evidence Extraction Protocol or I-DEEP, a novel protocol provides a framework to make the process of cybercrime investigation more agile using triaging and quick decision making by predictive analysis. This is accomplished by development and implementation of AI and Machine Learning algorithms.