An efficient intrusion detection systems in fog computing using forward selection and BiLSTM
Fadi Abu Zwayed,
Mohammed Anbar,
Selvakumar Manickam
et al.
Abstract:Intrusion detection systems (IDS) play a pivotal role in network security and anomaly detection and are significantly impacted by the feature selection (FS) process. As a significant task in machine learning and data analysis, FS is directed toward pinpointing a subset of pertinent features that primarily influence the target variable. This paper proposes an innovative approach to FS, leveraging the forward selection search algorithm with hybrid objective/fitness functions such as correlation, entropy, and var… Show more
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