SCVIC-CIDS-2021 was created using the raw data in CIC-IDS-2018*, while this new dataset, SCVIC-CIDS-2022 is formed from NDSec-1** meta-data by following a similar procedure.

 This dataset has been used in the following work:

J. Liu, M. Simsek, B. Kantarci, M. Bagheri, P. Djukic, "Bridging Networks and Hosts via Machine Learning-Based Intrusion Detection"; under review in IEEE Transactions on Dependable and Secure Computing.

China has a vast territory, and different regions have different air quality conditions. The database selects the air quality of 264 major cities in China as the research object.

A curated dataset containing underwater acoustic signals categorized into five different classes based on the vessel type: Cargo, Tanker, Tug, Passengership, and Background. Different subsets of data were generated from the original data considering the distance from the vessel to the hydrophone picking up the vessel's sound.

This method was motivated by the problem of multi-target switching tracking, such as the multi-target strike of weapons with vision sensors and the rapid multi-target grabbing of robots on industrial assembly lines. In recent years, various algorithms have been developed for trajectory planning and tracking. However, it is still challenging for unmanned servo system to capture dynamic targets quickly due to the constrains of motion performance, energy, and computational power.