The HiTar-23 Dataset Construction and Validation For Securing Industrial Internet of Things Environment

The increasing vulnerability of Industrial Internet of Things (IIoT) systems to cyber-attacks necessitates the development of dedicated datasets for robust intelligent security measures. This paper introduces the HiTar-23 dataset, designed to expedite the detection of cyber-attacks in industrial environments. The latter outlines the detailed steps involved in creating the HiTar-23 dataset, emphasizing meticulous methodologies for construction and validation threw the application of supervised machine learning (ML) techniques, specifically leveraging the WEKA 3.9.6 tool, to assess detection capabilities within a simulated industrial framework facilitated by the Arezzo environment. The holistic approach underscores careful dataset construction and sophisticated evaluation methods, providing insights to strengthen IIoT system security.