Preprocessed MQTTset for IoT Network Intrusion Detection (MLOps-Ready Dataset)

This dataset contains preprocessed network traffic derived from the publicly available MQTTset dataset for IoT intrusion detection. Specifically, version 5 (released on 2021-07-14) was used. The data has been transformed to support reproducible machine learning and MLOps workflows.

Key preprocessing steps include:

Synthetic temporal interleaving of attack packets within normal traffic to simulate realistic deployment conditions

Generation of multiple datasets for different stages of the ML lifecycle:

reference.csv: baseline normal traffic for creating pre-training tests

train.csv: mixed traffic with randomly injected attacks for model training

test.csv: mixed traffic with randomly injected attacks for model evaluation

post-deployment.csv: simulated production traffic with randomly injected attacks for evaluation

The dataset is intended for:

IoT intrusion detection model development

Data validation and monitoring experiments

Reproducible MLOps pipelines

Notes:

Attack timestamps are synthetically generated and do not reflect original capture timing

The dataset preserves the temporal structure of legitimate traffic