CICIDS-2017 dataset feature analysis with information gain for anomaly detection

• Main Authors: Kurniabudi, Kurniabudi, Stiawan, Deris, Darmawijoyo, Darmawijoyo, Idris, Mohd. Yazid, Bamhdi, Alwi M., Budiarto, Rahmat
• Format: Article
• Language: English
• Published: Institute of Electrical and Electronics Engineers Inc. 2020
• Subjects: QA75 Electronic computers. Computer science
• Online Access: http://eprints.utm.my/id/eprint/93850/1/CICIDS-MohdYazidIdris2020_CICIDS2017DatasetFeatureAnalysisWithInformation.pdf; http://eprints.utm.my/id/eprint/93850/; http://dx.doi.org/10.1109/ACCESS.2020.3009843

Feature selection (FS) is one of the important tasks of data preprocessing in data analytics. The data with a large number of features will affect the computational complexity, increase a huge amount of resource usage and time consumption for data analytics. The objective of this study is to analyze...