Performance Assessment of Supervised Classifiers for Designing Intrusion Detection Systems: A Comprehensive Review and Recommendations for Future Research

Performance Assessment of Supervised Classifiers for Designing Intrusion Detection Systems: A Comprehensive Review and Recommendations for Future Research

Supervised learning and pattern recognition is a crucial area of research in information retrieval, knowledge engineering, image processing, medical imaging, and intrusion detection. Numerous algorithms have been designed to address such complex application domains. Despite an enormous array of supe...

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Bibliographic Details
Main Authors: Ranjit Panigrahi, Samarjeet Borah, Akash Kumar Bhoi, Muhammad Fazal Ijaz, Moumita Pramanik, Rutvij H. Jhaveri, Chiranji Lal Chowdhary
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Mathematics
Subjects:
classifiers ranking
class-imbalance learning
IDS
IDS base learner
intrusion detection systems
network-based IDS
Online Access:https://www.mdpi.com/2227-7390/9/6/690

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