Genetic Algorithm based feature selection and Naïve Bayes for anomaly detection in fog computing environment-Reference-Cited by-同舟云学术

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Genetic Algorithm based feature selection and Naïve Bayes for anomaly detection in fog computing environment

Published:2021-12 Issue: Volume:6 Page:100156
ISSN:2666-8270
Container-title:Machine Learning with Applications
language:en
Short-container-title:Machine Learning with Applications

Author:

Onah John Oche^ORCID,Abdulhamid Shafi’i Muhammad^ORCID,Abdullahi Mohammed^ORCID,Hassan Ibrahim Hayatu^ORCID,Al-Ghusham Abdullah

Publisher

Elsevier BV

Subject

General Medicine

Reference41 articles.

1. Deep-IFS: Intrusion detection approach for IIoT traffic in fog environment;Abdel-Basset;IEEE Transactions on Industrial Informatics,2020

2. Fog computing and security issues: A review;Abdullah;International Conference on Computers Communications and Control,2018

3. Deep learning: The Frontier for distributed attack detection in fog-to-things computing;Abebe,2018

4. A user profile-aware policy based management framework for greening the cloud;Alhaddadin,2014

5. Network anomaly detection system using genetic algorithm and fuzzy logic;Anderson;Expert Systems with Applications,2018

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2. Intrusion detection system: a deep neural network-based concatenated approach;The Journal of Supercomputing;2024-03-12

3. Hybrid VGG19 and 2D-CNN for intrusion detection in the FOG-cloud environment;Expert Systems with Applications;2024-03

4. Hybrid wrapper feature selection method based on genetic algorithm and extreme learning machine for intrusion detection;Journal of Big Data;2024-02-01

5. Leveraging feature subset selection with deer hunting optimizer based deep learning for anomaly detection in secure cloud environment;Multimedia Tools and Applications;2024-01-20

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