{"title":"匿名通信系统流量识别与分类研究综述","authors":"Ruonan Wang, Yuefeng Zhao","doi":"10.1145/3503047.3503087","DOIUrl":null,"url":null,"abstract":"∗An anonymous communication system is an overlay network that hides the address of the destination server through multiple relay routing communications. As communication entities are difficult to track and locate, a large number of harmful social security activities such as leakage of personal information, drug dealings, and terrorist activities have occurred. Traffic recognition technology can locate illegal activities from anonymous user communications and help law enforcement agencies investigate criminal activities on the darknet. Currently, the existing research mainly focuses on traditional traffic classification, encrypted traffic analysis, and tor traffic identification, but there is a lack of comprehensive research and investigation on darknet traffic identification. This paper summarizes darknet traffic classification methods based on deep learning and machine learning, reviews common public data sets, and discusses open problems and challenges in this field.","PeriodicalId":190604,"journal":{"name":"Proceedings of the 3rd International Conference on Advanced Information Science and System","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Survey on Anonymous Communication Systems Traffic Identification and Classification\",\"authors\":\"Ruonan Wang, Yuefeng Zhao\",\"doi\":\"10.1145/3503047.3503087\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"∗An anonymous communication system is an overlay network that hides the address of the destination server through multiple relay routing communications. As communication entities are difficult to track and locate, a large number of harmful social security activities such as leakage of personal information, drug dealings, and terrorist activities have occurred. Traffic recognition technology can locate illegal activities from anonymous user communications and help law enforcement agencies investigate criminal activities on the darknet. Currently, the existing research mainly focuses on traditional traffic classification, encrypted traffic analysis, and tor traffic identification, but there is a lack of comprehensive research and investigation on darknet traffic identification. This paper summarizes darknet traffic classification methods based on deep learning and machine learning, reviews common public data sets, and discusses open problems and challenges in this field.\",\"PeriodicalId\":190604,\"journal\":{\"name\":\"Proceedings of the 3rd International Conference on Advanced Information Science and System\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 3rd International Conference on Advanced Information Science and System\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3503047.3503087\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 3rd International Conference on Advanced Information Science and System","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3503047.3503087","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Survey on Anonymous Communication Systems Traffic Identification and Classification
∗An anonymous communication system is an overlay network that hides the address of the destination server through multiple relay routing communications. As communication entities are difficult to track and locate, a large number of harmful social security activities such as leakage of personal information, drug dealings, and terrorist activities have occurred. Traffic recognition technology can locate illegal activities from anonymous user communications and help law enforcement agencies investigate criminal activities on the darknet. Currently, the existing research mainly focuses on traditional traffic classification, encrypted traffic analysis, and tor traffic identification, but there is a lack of comprehensive research and investigation on darknet traffic identification. This paper summarizes darknet traffic classification methods based on deep learning and machine learning, reviews common public data sets, and discusses open problems and challenges in this field.