Anomaly Detection; Network Security; Intrusion Detection System ; Machine Learning ; Payload ; Dataset; IoT;
The dataset includes 2 datasets. The first one is Australian Electricity Load and Price Forecasting dataset, which includes the hourly electricity load and dry bulb temperature, dew point temperature, wet bulb temperature, humidity, and electricity price in Australia from 2006 to 2010. The other is the GEFCom2014 dataset, which provides hourly historical load and weather data for utilities from 2006 to 2014.
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The Unified Multimodal Network Intrusion Detection System (UM-NIDS) dataset is a comprehensive, standardized dataset that integrates network flow data, packet payload information, and contextual features, making it highly suitable for machine learning-based intrusion detection models. This dataset addresses key limitations in existing NIDS datasets, such as inconsistent feature sets and the lack of payload or time-window-based contextual features.
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