{"title":"使用机器学习方法的僵尸网络检测特征表示","authors":"P. C. Tikekar, S. Sherekar, V. Thakre","doi":"10.1109/iccica52458.2021.9697320","DOIUrl":null,"url":null,"abstract":"Over the past ten years, Botnet has been an emerging threat that is increasing day by day & has gained popularity amongst researchers. Botnet detection is a very challenging task, so great Scientific research efforts have been made to develop effective & efficient techniques to detect the presence of Botnet. For developing the Botnet detection technique, most of the researchers use machine learning. Sometimes due to the C&C nature of Botnet & various characteristics of different types of bots, it becomes challenging to identify the Botnet. This paper studies & analyze multiple features of Botnet in machine learning techniques responsible for the detection. The paper discusses various Botnet features with their type, traffic parameters, databases, and the Botnet Detection method's parameters essential to test the results. The researcher needs to analyze the existing Botnet detection technique with its databases & parameters to develop a better detection technique.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Features Representation of Botnet Detection Using Machine Learning Approaches\",\"authors\":\"P. C. Tikekar, S. Sherekar, V. Thakre\",\"doi\":\"10.1109/iccica52458.2021.9697320\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Over the past ten years, Botnet has been an emerging threat that is increasing day by day & has gained popularity amongst researchers. Botnet detection is a very challenging task, so great Scientific research efforts have been made to develop effective & efficient techniques to detect the presence of Botnet. For developing the Botnet detection technique, most of the researchers use machine learning. Sometimes due to the C&C nature of Botnet & various characteristics of different types of bots, it becomes challenging to identify the Botnet. This paper studies & analyze multiple features of Botnet in machine learning techniques responsible for the detection. The paper discusses various Botnet features with their type, traffic parameters, databases, and the Botnet Detection method's parameters essential to test the results. The researcher needs to analyze the existing Botnet detection technique with its databases & parameters to develop a better detection technique.\",\"PeriodicalId\":327193,\"journal\":{\"name\":\"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)\",\"volume\":\"26 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iccica52458.2021.9697320\",\"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 International Conference on Computational Intelligence and Computing Applications (ICCICA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iccica52458.2021.9697320","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Features Representation of Botnet Detection Using Machine Learning Approaches
Over the past ten years, Botnet has been an emerging threat that is increasing day by day & has gained popularity amongst researchers. Botnet detection is a very challenging task, so great Scientific research efforts have been made to develop effective & efficient techniques to detect the presence of Botnet. For developing the Botnet detection technique, most of the researchers use machine learning. Sometimes due to the C&C nature of Botnet & various characteristics of different types of bots, it becomes challenging to identify the Botnet. This paper studies & analyze multiple features of Botnet in machine learning techniques responsible for the detection. The paper discusses various Botnet features with their type, traffic parameters, databases, and the Botnet Detection method's parameters essential to test the results. The researcher needs to analyze the existing Botnet detection technique with its databases & parameters to develop a better detection technique.