Comparative analysis of SVM Kernels and Parameters for Efficient Anomaly Detection in IoT

Author:

Agrawal Akhileshwar Prasad1,Singh Nanhay2

Affiliation:

1. AIACT&R (now NSUT East Campus), GGSIPU,Dept. of CSE,Delhi,India

2. AIACT&R (now NSUT East Campus),Dept. of CSE,Delhi,India

Publisher

IEEE

Cited by 5 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. Machine Learning for Blockchain and IoT Systems in Smart Cities: A Survey;Future Internet;2024-09-06

2. Anomaly detection using deep learning approach for IoT smart city applications;Multimedia Tools and Applications;2024-07-06

3. Comparative study between ML approaches in Intrusion Detection Context;2023 IEEE Afro-Mediterranean Conference on Artificial Intelligence (AMCAI);2023-12-13

4. Comparative Analysis of the Performance of Various Support Vector Machine kernels;2022 5th Information Technology for Education and Development (ITED);2022-11-01

5. A two-stage stacked ensemble intrusion detection system using five base classifiers and MLP with optimal feature selection;Microprocessors and Microsystems;2022-10

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