What is it about?
An enhanced ResNet architecture for feature extraction is proposed which extracts more deep features from given traffic traces. An improved quantum query optimization (IQQO) algorithm for is used feature selection to selects optimal best among multiple features which reduces the data dimensionality issues.
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Why is it important?
The selected feature extraction has given to the detection and classification module to classify the traffic traces are affected by intrusion or not. A fast and accurate intrusion detection mechanism, named as hybrid deep learning technique which combines convolutional neural network (CNN) and diagonal XG boosting (CNN-DigXG) for the fast and accurate intrusion detection in IoT network is implemented.
Perspectives
Writing this article was a great pleasure as it has co-authors with whom I have had long standing collaborations. . A fast and accurate intrusion detection mechanism, hybrid deep learning technique which combines convolutional neural network (CNN) and diagonal XG boosting (CNN-DigXG) for the fast and accurate intrusion detection in IoT network. The Optimal Secure Defense-Intrusion Detection System (OSD-IDS) mechanism is very effective compared to the state-of-art IDS mechanisms.
J S. Prasath
Bharat Institute of Engineering and Technology
Read the Original
This page is a summary of: An optimal secure defense mechanism for DDoS attack in IoT network using feature optimization and intrusion detection system, Journal of Intelligent & Fuzzy Systems, March 2024, IOS Press,
DOI: 10.3233/jifs-235529.
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