Analysis of Extreme Learning Machines (ELMs) for intelligent intrusion detection systems: A survey
- 27 May 2024
- journal article
- review article
- Published by Elsevier in Expert Systems with Applications
- Vol. 253
Abstract
No abstract availableKeywords
This publication has 118 references indexed in Scilit:
- Analysis, characterization, prediction, and attribution of extreme atmospheric events with machine learning and deep learning techniques: a reviewTheoretical and Applied Climatology, 2023
- Explainable machine learning for phishing feature detectionQuality and Reliability Engineering International, 2023
- An intelligent identification and classification system for malicious uniform resource locators (URLs)Neural Computing and Applications, 2023
- Explainable AI methods in cyber risk managementQuality and Reliability Engineering International, 2021
- A review on extreme learning machineMultimedia Tools and Applications, 2021
- Improving Extreme Learning Machine Accuracy Utilizing Genetic Algorithm for Intrusion Detection Purposes2021
- BotDetector: An extreme learning machine‐based Internet of Things botnet detection modelTransactions on Emerging Telecommunications Technologies, 2020
- Wireless sensor network intrusion detection system based on MK-ELMSoft Computing, 2020
- A Review of Advances in Extreme Learning Machine Techniques and Its Applications2017
- An efficient cascaded method for network intrusion detection based on extreme learning machinesThe Journal of Supercomputing, 2016