An Efficient Hybridization of K-Means and Genetic Algorithm Based on Support Vector Machine for Cyber Intrusion Detection System
Author:
Publisher
School of Electrical Engineering and Informatics (STEI) ITB
Subject
General Engineering
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Intrusion detection systems for IoT based on bio-inspired and machine learning techniques: a systematic review of the literature;Cluster Computing;2024-04-14
2. Modified genetic algorithm and fine-tuned long short-term memory network for intrusion detection in the internet of things networks with edge capabilities;Applied Soft Computing;2024-04
3. GADNN: a revolutionary hybrid deep learning neural network for age and sex determination utilizing cone beam computed tomography images of maxillary and frontal sinuses;BMC Medical Research Methodology;2024-02-27
4. Improving Network Intrusion Detection Performance : An Empirical Evaluation Using Extreme Gradient Boosting (XGBoost) with Recursive Feature Elimination;2024 IEEE 3rd International Conference on AI in Cybersecurity (ICAIC);2024-02-07
5. CTSF: An Intrusion Detection Framework for Industrial Internet Based on Enhanced Feature Extraction and Decision Optimization Approach;Sensors;2023-10-28
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