We leveraged the ToN-IoT dataset, utilizing both the IoT device dataset and the Network dataset contained within, to propose a novel approach that integrates multiple datasets for replicating complex IoT scenarios. Pioneeringly, we introduced the use of sine and cosine component cyclic encoding for ...
Such IDSs require an updated and representative IoT dataset for training and evaluation. However, there is a lack of benchmark IoT and IIoT datasets for assessing IDSs-enabled IoT systems. This paper addresses this issue and proposes a new data-driven IoT/IIoT dataset with the ground truth ...
The TON_IoT network dataset is validated using four machine learning-based intrusion detection algorithms of Gradient Boosting Machine, Random Forest, Naive Bayes, and Deep Neural Networks, revealing a high performance of detection accuracy using the set of training and testing. A comparative summary ...
In this paper, we introduce the description, statistical analysis, and machine learning evaluation of the novel ToN_IoT dataset. Comparison to other recent IoT datasets shows the importance of heterogeneity within these datasets, and how differences between datasets may have a huge impact on ...