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Kuku, Oyeyemi, Chrysikos, Alexandros and Salekzamankhani, Shahram (2025) Digital forensic readiness in IoT-enabled organisations: forensic investigation analysis in real-time. In: ICDAM 2024: International Conference on Data Analytics & Management, 14-15 June 024, London.
The increased use of IoT applications across organisations poses multiple challenges for data security and protection. Security analysis using forensic techniques is essential for organisations to understand the security issues and potential data breaches in IoT devices. Organisations must develop and include digital forensic readiness mechanisms in their overall data security and IT policies. The need is critical as security breaches globally are reported through IoT devices and networks. With its practical implications, this research analyses real-time readiness models for IoT-enabled organisations for forensic investigation analysis and finds how implementing DFR programs can help organisations prepare for digital investigations in advance, thus reducing costs and improving incident responses and a readiness plan to mitigate potential attacks. The research provides a practical DFR model to include the ISO standards in organisational processes, data security IoT networks, and processes for IoT security, as well as a readiness model to include in the overall security management policies for organisations. Different methodologies and designs for building DFR models, which include certification and legal processes, forensic tools, data handling and DFR preparedness in any organisation, are explored and explained. An organisational network structure that includes DFR readiness in an IoT environment is provided as an example. Importantly, the security management processes and DFR processes must be concurrent to have robust data protection and avoid data breaches. Analysis indicates that strengthening DFR capabilities is crucial to minimising the impact of cyber incidents, such as downtime, financial losses, and damage to reputation. However, effective DFR requires careful planning and assessment to work correctly in different organisational settings. Ongoing research is essential to refine the DFR model and evaluate its performance in real-world investigations.
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