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Information Systems and Technology

Permanent URI for this communityhttps://hdl.handle.net/10413/6786

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Browsing Information Systems and Technology by Subject "Artificial Intelligence."

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    The acceptance of chatbot technology to support academic activity at the University of KwaZulu-Natal.
    (2023) Johnson, Ebunoluwa Ehikowoicho.; Ranjeeth, Sanjay.
    Abstract available in PDF.
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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.