{"title":"无线网络入侵检测系统","authors":"Baimukashev Rashid, Kamalkhan Artykbayev, Kazybek Adam, Begenov Mels","doi":"10.1109/icecco53203.2021.9663787","DOIUrl":null,"url":null,"abstract":"The network security plays a vital role in the performance of the wireless networks, and as a part of network security features the intrusion detection system may enhance the performance of the network. In our project we designed such intrusion detection system using deep learning approaches such as CNN, RNN and LSTM as well as with traditional machine learning algorithms such as SVM, Random Forest and XGBoost. In our project we achieved a near to state-of-the-art performance on detecting network attacks on the NSL-KDD dataset.","PeriodicalId":331369,"journal":{"name":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2021-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intrusion Detection System for Wireless Networks\",\"authors\":\"Baimukashev Rashid, Kamalkhan Artykbayev, Kazybek Adam, Begenov Mels\",\"doi\":\"10.1109/icecco53203.2021.9663787\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The network security plays a vital role in the performance of the wireless networks, and as a part of network security features the intrusion detection system may enhance the performance of the network. In our project we designed such intrusion detection system using deep learning approaches such as CNN, RNN and LSTM as well as with traditional machine learning algorithms such as SVM, Random Forest and XGBoost. In our project we achieved a near to state-of-the-art performance on detecting network attacks on the NSL-KDD dataset.\",\"PeriodicalId\":331369,\"journal\":{\"name\":\"2021 16th International Conference on Electronics Computer and Computation (ICECCO)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 16th International Conference on Electronics Computer and Computation (ICECCO)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/icecco53203.2021.9663787\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 16th International Conference on Electronics Computer and Computation (ICECCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/icecco53203.2021.9663787","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
网络安全对无线网络的性能起着至关重要的作用，入侵检测系统作为网络安全特征的一部分，可以提高网络的性能。在我们的项目中，我们使用CNN, RNN和LSTM等深度学习方法以及传统的机器学习算法(如SVM, Random Forest和XGBoost)设计了这样的入侵检测系统。在我们的项目中，我们在检测NSL-KDD数据集上的网络攻击方面取得了接近最先进的性能。
The network security plays a vital role in the performance of the wireless networks, and as a part of network security features the intrusion detection system may enhance the performance of the network. In our project we designed such intrusion detection system using deep learning approaches such as CNN, RNN and LSTM as well as with traditional machine learning algorithms such as SVM, Random Forest and XGBoost. In our project we achieved a near to state-of-the-art performance on detecting network attacks on the NSL-KDD dataset.
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