Cascaded hybrid intrusion detection model based on SOM and RBF neural networks-Reference-Cited by-同舟云学术

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Cascaded hybrid intrusion detection model based on SOM and RBF neural networks

Published:2019-03-07 Issue:21 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Almiani Muder¹^ORCID,AbuGhazleh Alia²,Al‐Rahayfeh Amer³,Razaque Abdul⁴

Affiliation:

1. Department of Computer Information Systems Al‐Hussein Bin Talal University Ma'an Jordan

2. Jordan University 11942‐13375 Amman Jordan

3. Department of Computer Science Al‐Hussein Bin Talal University Ma'an Jordan

4. Department of Computer Science New York Institute of Technology New York

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5233

Reference56 articles.

1. Almi'aniM GhazlehAA Al‐RahayfehA RazaqueA.Intelligent intrusion detection system using clustered self organized map. Paper presented at: 2018 5th International Conference on Software Defined Systems (SDS);2018;Barcelona Spain.

2. CLUSTERING-BASED NETWORK INTRUSION DETECTION

3. CANN: An intrusion detection system based on combining cluster centers and nearest neighbors

4. TahirHM SaidAM OsmanNH ZakariaNH SabriPNAM KatukN.Oving K‐means clustering using discretization technique in network intrusion detection system. Paper presented at: 2016 3rd International Conference on Computer and Information Sciences (ICCOINS);2016;Kuala Lumpur Malaysia.

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1. Hybrid intelligent technique for intrusion detection in cyber physical systems with improved feature set;Journal of Intelligent & Fuzzy Systems;2023-12-15

2. An Effective Anomaly Detection Model Combined Feature Selection with Improved CNN in SDN;2023 3rd Asia-Pacific Conference on Communications Technology and Computer Science (ACCTCS);2023-02

3. Intrusion detection in cyber–physical environment using hybrid Naïve Bayes—Decision table and multi-objective evolutionary feature selection;Computer Communications;2022-04

4. Two-step ensemble approach for intrusion detection and identification in IoT and fog computing environments;Computers & Electrical Engineering;2022-03

5. Securing Bio-Cyber Interface for the Internet of Bio-Nano Things using Particle Swarm Optimization and Artificial Neural Networks based parameter profiling;Computers in Biology and Medicine;2021-09

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