Computer networks anomaly detection by using PCA & pattern recognition
The detection of anomalies in computer networks is one of the most considerable challenges that experts in this field are facing nowadays. Thus far, different artificial intelligence methods and algorithms have been proposed, tested, and utilized for detecting these anomalies. However, attempts made...
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| Format: | Article |
| Language: | English |
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Qom University of Technology
2025-06-01
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| Series: | Mathematics and Computational Sciences |
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| Online Access: | https://mcs.qut.ac.ir/article_724815_af4b37b630e69872ff0c4c721fc8f78a.pdf |
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| author | Elham Bideh Javad Vahidi |
| author_facet | Elham Bideh Javad Vahidi |
| author_sort | Elham Bideh |
| collection | DOAJ |
| description | The detection of anomalies in computer networks is one of the most considerable challenges that experts in this field are facing nowadays. Thus far, different artificial intelligence methods and algorithms have been proposed, tested, and utilized for detecting these anomalies. However, attempts made to enhance the speed and accuracy of these anomalies’ detection process are continuously ongoing. In this research, pattern recognition based on artificial neural networks is applied to automatically detect anomalies in computer networks. Also, to increase the speed of the pattern recognition based on the process of the neural network, the principal component analysis algorithm will be used as a method for dimension reduction of training samples. The results of the performed simulations based on the proposed methods in this research show that dimension reduction of training samples by principal component analysis algorithm and then applying the pattern recognition based on neural networks method leads to high-speed (less than 10 seconds) and high-accuracy (99-100%) detection of anomalies in computer networks. |
| format | Article |
| id | doaj-art-77c93ea2c8554963b4a33d1a761a27c8 |
| institution | Matheson Library |
| issn | 2717-2708 |
| language | English |
| publishDate | 2025-06-01 |
| publisher | Qom University of Technology |
| record_format | Article |
| series | Mathematics and Computational Sciences |
| spelling | doaj-art-77c93ea2c8554963b4a33d1a761a27c82025-07-08T11:57:56ZengQom University of TechnologyMathematics and Computational Sciences2717-27082025-06-0162779110.30511/mcs.2025.2052129.1301724815Computer networks anomaly detection by using PCA & pattern recognitionElham Bideh0Javad Vahidi1Master Science of Computer Networks, Shomal University, Amol, IranDepartment of Computer Science, Iran University of Science and Technology, Tehran, IranThe detection of anomalies in computer networks is one of the most considerable challenges that experts in this field are facing nowadays. Thus far, different artificial intelligence methods and algorithms have been proposed, tested, and utilized for detecting these anomalies. However, attempts made to enhance the speed and accuracy of these anomalies’ detection process are continuously ongoing. In this research, pattern recognition based on artificial neural networks is applied to automatically detect anomalies in computer networks. Also, to increase the speed of the pattern recognition based on the process of the neural network, the principal component analysis algorithm will be used as a method for dimension reduction of training samples. The results of the performed simulations based on the proposed methods in this research show that dimension reduction of training samples by principal component analysis algorithm and then applying the pattern recognition based on neural networks method leads to high-speed (less than 10 seconds) and high-accuracy (99-100%) detection of anomalies in computer networks.https://mcs.qut.ac.ir/article_724815_af4b37b630e69872ff0c4c721fc8f78a.pdfcomputer networks anomaly detectionpattern recognitionartificial neural networksback propagation algorithmprincipal component analysis |
| spellingShingle | Elham Bideh Javad Vahidi Computer networks anomaly detection by using PCA & pattern recognition Mathematics and Computational Sciences computer networks anomaly detection pattern recognition artificial neural networks back propagation algorithm principal component analysis |
| title | Computer networks anomaly detection by using PCA & pattern recognition |
| title_full | Computer networks anomaly detection by using PCA & pattern recognition |
| title_fullStr | Computer networks anomaly detection by using PCA & pattern recognition |
| title_full_unstemmed | Computer networks anomaly detection by using PCA & pattern recognition |
| title_short | Computer networks anomaly detection by using PCA & pattern recognition |
| title_sort | computer networks anomaly detection by using pca pattern recognition |
| topic | computer networks anomaly detection pattern recognition artificial neural networks back propagation algorithm principal component analysis |
| url | https://mcs.qut.ac.ir/article_724815_af4b37b630e69872ff0c4c721fc8f78a.pdf |
| work_keys_str_mv | AT elhambideh computernetworksanomalydetectionbyusingpcapatternrecognition AT javadvahidi computernetworksanomalydetectionbyusingpcapatternrecognition |