INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS
Network intrusion is any unauthorized activity on a computer network. Attacks on the network computer system can be devastating and affect networks and company establishments. Therefore, it is necessary to curb these attacks. Network Intrusion Detection System (NIDS) contributes to recognizing the a...
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| Format: | Article |
| Language: | English |
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Universitas Pattimura
2022-03-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4205 |
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| author | Muhammad Ahsan Arif Khoirul Anam Erdi Julian Andi Indra Jaya |
| author_facet | Muhammad Ahsan Arif Khoirul Anam Erdi Julian Andi Indra Jaya |
| author_sort | Muhammad Ahsan |
| collection | DOAJ |
| description | Network intrusion is any unauthorized activity on a computer network. Attacks on the network computer system can be devastating and affect networks and company establishments. Therefore, it is necessary to curb these attacks. Network Intrusion Detection System (NIDS) contributes to recognizing the attacks or intrusions. This paper explains the factors that influence network attacks. Some machine learning methods are used such as are logistic regression, random forest XGBoost, and CatBoost. The best model is chosen from these models based on its accuracy level. Classification modeling is divided into two types, namely using a dummy and not using dummy variables. The best method for predicting network intrusion is a random forest with a dummy variable that has an Area Under Curve (AUC) value of 92.31% and an accuracy of 90.38%. |
| format | Article |
| id | doaj-art-169f36d62ffb49989fb79e189deb9b3e |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2022-03-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-169f36d62ffb49989fb79e189deb9b3e2025-08-20T03:36:12ZengUniversitas PattimuraBarekeng1978-72272615-30172022-03-0116105706410.30598/barekengvol16iss1pp057-0644205INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMSMuhammad Ahsan0Arif Khoirul Anam1Erdi Julian2Andi Indra Jaya3Statistics Department, Faculty of Science and Analytic Data, Institut Teknologi Sepuluh NopemberStatistics Department, Faculty of Science and Analytic Data, Institut Teknologi Sepuluh NopemberStatistics Department, Faculty of Science and Analytic Data, Institut Teknologi Sepuluh NopemberStatistics Department, Faculty of Science and Analytic Data, Institut Teknologi Sepuluh NopemberNetwork intrusion is any unauthorized activity on a computer network. Attacks on the network computer system can be devastating and affect networks and company establishments. Therefore, it is necessary to curb these attacks. Network Intrusion Detection System (NIDS) contributes to recognizing the attacks or intrusions. This paper explains the factors that influence network attacks. Some machine learning methods are used such as are logistic regression, random forest XGBoost, and CatBoost. The best model is chosen from these models based on its accuracy level. Classification modeling is divided into two types, namely using a dummy and not using dummy variables. The best method for predicting network intrusion is a random forest with a dummy variable that has an Area Under Curve (AUC) value of 92.31% and an accuracy of 90.38%.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4205classificationintrusionmachine learningnetwork |
| spellingShingle | Muhammad Ahsan Arif Khoirul Anam Erdi Julian Andi Indra Jaya INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS Barekeng classification intrusion machine learning network |
| title | INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS |
| title_full | INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS |
| title_fullStr | INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS |
| title_full_unstemmed | INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS |
| title_short | INTERPRETABLE PREDICTIVE MODEL OF NETWORK INTRUSION USING SEVERAL MACHINE LEARNING ALGORITHMS |
| title_sort | interpretable predictive model of network intrusion using several machine learning algorithms |
| topic | classification intrusion machine learning network |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/4205 |
| work_keys_str_mv | AT muhammadahsan interpretablepredictivemodelofnetworkintrusionusingseveralmachinelearningalgorithms AT arifkhoirulanam interpretablepredictivemodelofnetworkintrusionusingseveralmachinelearningalgorithms AT erdijulian interpretablepredictivemodelofnetworkintrusionusingseveralmachinelearningalgorithms AT andiindrajaya interpretablepredictivemodelofnetworkintrusionusingseveralmachinelearningalgorithms |