DoS Attacks, Human Factors, and Evidence Extraction for the Industrial Internet of Things (IIoT) Paradigm

The unique characteristics of IIoT, including hetero-geneity, existence of legacy infrastructure, and critical operational requirements, demand for tailored approaches to better compre-hend and address security threats. A comprehensive investigation into the modelling and analysis of DoS attacks in IIoT is presented. Our research focuses on developing a DoS attack model for IIoT networks, facilitating effective analysis and response strategies. Additionally, we explore the mapping of these attacks to the MITRE ATT&CK framework, conduct simulations for attack scenarios, and collect data for analysis. By addressing the existing research gaps in DoS attack modelling for IIoT networks, such as limited research on Modbus TCP communications, lack of artifact extraction models, and mapping attacks to MITRE, we present standardization of attack modeling. Our simulation platform encompasses physical processes, controllers, and devices interacting with each other, provides multidimensional data for artifact extraction, fosters forensic investigations and analysis of attack impact. Overall, this research provides a deeper understanding of DoS attack vectors and vulnerabilities specific to IIoT networks, standardizes attack categorization and analysis through the MITRE framework, and facilitates deeper exploration of attack characteristics and behavior for digital forensic readiness.