Enhancing anomaly detection: A comprehensive approach with MTBO feature selection and TVETBO Optimized Quad-LSTM classification-Reference-Cited by-同舟云学术

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Enhancing anomaly detection: A comprehensive approach with MTBO feature selection and TVETBO Optimized Quad-LSTM classification

Published:2024-10 Issue: Volume:119 Page:109536
ISSN:0045-7906
Container-title:Computers and Electrical Engineering
language:en
Short-container-title:Computers and Electrical Engineering

Author:

Reddy N V RajaSekhar^ORCID,N SreeDivya,B．N Jagadesh,Gandikota Ramu,Lella Kranthi Kumar^ORCID,Pydala Bhasha,Vatambeti Ramesh^ORCID

Publisher

Elsevier BV

Reference49 articles.

1. Energy efficient and high-speed error control scheme for real time wireless sensor networks;Barati;Int J Distrib Sens Netw,2014

2. Network anomaly detection using deep learning techniques;Hooshmand;CAAI Transactions on Intellig Technol,2022

3. A novel approach for faulty node detection with the aid of fuzzy theory and majority voting in wireless sensor networks;Javanmardi;Int J Adv Smart Sensor Network Syst,2012

4. An empirical evaluation of deep learning for network anomaly detection;Malaiya;IEEE Access,2019

5. Anomaly-based intrusion detection system in the Internet of Things using a convolutional neural network and multi-objective enhanced Capuchin Search Algorithm;Asgharzadeh;J Parallel Distrib Comput,2023

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