The TON_IoT datasets are new generations of Internet of Things (IoT) and Industrial IoT (IIoT) datasets for evaluating the fidelity and efficiency of different cybersecurity applications based on Artificial Intelligence (AI). The datasets have been calle
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 ...
Evaluating the network ToN_IoT dataset using variousmachine learningmodels to assess its credibility. Abstract While there has been a significant interest in understanding the cyber threat landscape of Internet of Things (IoT) networks, and the design ofArtificial Intelligence(AI)-based security approach...
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 ...
About Dataset NF-ToN-IoT-V2 is the extended NetFlow version of NF-ToN-IoT. Compared to the original NF-NIDS datasets, the feature set of NetFlow features has expanded from 8 to 43. This is one dataset in the NFV2-collection by the university of Queensland aimed at standardizing network-...