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A review of recent approaches on wrapper feature selection for intrusion detection
In this paper, we present a review of recent advances in wrapper feature selection
techniques for attack detection and classification, applied in intrusion detection area. Due to …
techniques for attack detection and classification, applied in intrusion detection area. Due to …
Building an efficient intrusion detection system based on feature selection and ensemble classifier
Y Zhou, G Cheng, S Jiang, M Dai - Computer networks, 2020 - Elsevier
Intrusion detection system (IDS) is one of extensively used techniques in a network topology
to safeguard the integrity and availability of sensitive assets in the protected systems …
to safeguard the integrity and availability of sensitive assets in the protected systems …
Deep learning in IoT intrusion detection
Abstract The Internet of Things (IoT) is the new paradigm of our times, where smart devices
and sensors from across the globe are interconnected in a global grid, and distributed …
and sensors from across the globe are interconnected in a global grid, and distributed …
Feature selection and ensemble-based intrusion detection system: an efficient and comprehensive approach
E Jaw, X Wang - Symmetry, 2021 - mdpi.com
The emergence of ground-breaking technologies such as artificial intelligence, cloud
computing, big data powered by the Internet, and its highly valued real-world applications …
computing, big data powered by the Internet, and its highly valued real-world applications …
Ensemble classifiers for network intrusion detection using a novel network attack dataset
Due to the extensive use of computer networks, new risks have arisen, and improving the
speed and accuracy of security mechanisms has become a critical need. Although new …
speed and accuracy of security mechanisms has become a critical need. Although new …
[HTML][HTML] An improved binary manta ray foraging optimization algorithm based feature selection and random forest classifier for network intrusion detection
The growth within the Internet and communications areas have led to a massive surge in the
dimension of network and data. Consequently, several new threats are being created and …
dimension of network and data. Consequently, several new threats are being created and …
[HTML][HTML] Augmentation in performance and security of WSNs for IoT applications using feature selection and classification techniques
R Yadav, I Sreedevi, D Gupta - Alexandria Engineering Journal, 2023 - Elsevier
Energy consumption, secure connection of Sensor Nodes (SNs), and their performance
analysis play a major role in Wireless Sensor Networks (WSNs) research. Increased case …
analysis play a major role in Wireless Sensor Networks (WSNs) research. Increased case …
χ2-BidLSTM: A Feature Driven Intrusion Detection System Based on χ2 Statistical Model and Bidirectional LSTM
In a network architecture, an intrusion detection system (IDS) is one of the most commonly
used approaches to secure the integrity and availability of critical assets in protected …
used approaches to secure the integrity and availability of critical assets in protected …
A framework to detect DDoS attack in Ryu controller based software defined networks using feature extraction and classification
Abstract Software Defined Network (SDN) is an emerging network architecture and is being
used in many IT industries and academia. Its popularity in the present age has attracted …
used in many IT industries and academia. Its popularity in the present age has attracted …
Cybersecurity anomaly detection: Ai and ethereum blockchain for a secure and tamperproof ioht data management
The Internet of Healthcare Things (IoHT) is an emerging critical technology for managing
patients' health. They are prone to cybersecurity vulnerabilities because they are connected …
patients' health. They are prone to cybersecurity vulnerabilities because they are connected …