{"title":"基于流动特性的长时流分类及应用","authors":"Zihao Chen, Wei Ding, Weijian Sun, Liang Xu","doi":"10.1109/CSP58884.2023.00009","DOIUrl":null,"url":null,"abstract":"Long-duration flows are extended network flows in the Internet that result from various network activities such as file transfers, persistent connections, and control command transmissions. These flows are utilized by a broad range of applications in the Internet, both benign and malicious, and their management and security are crucial for the functioning of the Internet. In this study, we categorize long-duration flows into three types: control flows, mixed flows, and information flows, based on their purpose for existence. Subsequently, features are extracted based on three characteristics: flow, time series, and packet length. The selected features are used to construct a dataset for training a classification model. The empirical analysis of real-world traffic data from high-speed network boundaries demonstrates that the classification model is capable of accurately identifying control flows in long-duration flows and determining specific applications within them.","PeriodicalId":255083,"journal":{"name":"2023 7th International Conference on Cryptography, Security and Privacy (CSP)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification and Application of Long-duration Flows Based on Flow Behavior\",\"authors\":\"Zihao Chen, Wei Ding, Weijian Sun, Liang Xu\",\"doi\":\"10.1109/CSP58884.2023.00009\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Long-duration flows are extended network flows in the Internet that result from various network activities such as file transfers, persistent connections, and control command transmissions. These flows are utilized by a broad range of applications in the Internet, both benign and malicious, and their management and security are crucial for the functioning of the Internet. In this study, we categorize long-duration flows into three types: control flows, mixed flows, and information flows, based on their purpose for existence. Subsequently, features are extracted based on three characteristics: flow, time series, and packet length. The selected features are used to construct a dataset for training a classification model. The empirical analysis of real-world traffic data from high-speed network boundaries demonstrates that the classification model is capable of accurately identifying control flows in long-duration flows and determining specific applications within them.\",\"PeriodicalId\":255083,\"journal\":{\"name\":\"2023 7th International Conference on Cryptography, Security and Privacy (CSP)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 7th International Conference on Cryptography, Security and Privacy (CSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CSP58884.2023.00009\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 7th International Conference on Cryptography, Security and Privacy (CSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSP58884.2023.00009","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Classification and Application of Long-duration Flows Based on Flow Behavior
Long-duration flows are extended network flows in the Internet that result from various network activities such as file transfers, persistent connections, and control command transmissions. These flows are utilized by a broad range of applications in the Internet, both benign and malicious, and their management and security are crucial for the functioning of the Internet. In this study, we categorize long-duration flows into three types: control flows, mixed flows, and information flows, based on their purpose for existence. Subsequently, features are extracted based on three characteristics: flow, time series, and packet length. The selected features are used to construct a dataset for training a classification model. The empirical analysis of real-world traffic data from high-speed network boundaries demonstrates that the classification model is capable of accurately identifying control flows in long-duration flows and determining specific applications within them.