{"title":"Voip-Over- Vpn的分类与防范研究","authors":"Liu Chaoqun, Luo Jie, Dong Bin","doi":"10.1109/ICIM56520.2022.00019","DOIUrl":null,"url":null,"abstract":"With the development of IP technology, VoIP(Voice over IP) service is the most popular voice communication mode in the world. At the same time, more and more individual and enterprise users use VPN s to encrypt transmitted content to protect communication privacy. However, the operators and CSPs(Carrier Service Provider) are interested in their subscribers who used VoIP-Over- Vpntechnology, since it will result in their huge revenue loss while the subscribers escaped the high voice charging. To solve this problem, this paper develops a mechanism to detect and mitigate the VOIP-over- VPN traffic to protect the revenue for the telecommunication industry. In this paper, an advanced packet matching engine is introduced to extract traffic packet features and flow features from encrypted VOIP traffic, and input them into an intelligent detection engine based on heuristic algorithm to identify and classify voIP-over- VPN traffic. Based on the identification and classification results, an Action engine is introduced to block, shape, charge or report the event records. Through plenty of experiments and practices, the VOIP-over-VPN detection and mitigation solution proposed in this paper can achieve more than 95% detection accuracy, and can be alleviated according to different mitigation policies.","PeriodicalId":391964,"journal":{"name":"2022 8th International Conference on Information Management (ICIM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Research on Voip-Over- Vpn s Classification And Mitigation\",\"authors\":\"Liu Chaoqun, Luo Jie, Dong Bin\",\"doi\":\"10.1109/ICIM56520.2022.00019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the development of IP technology, VoIP(Voice over IP) service is the most popular voice communication mode in the world. At the same time, more and more individual and enterprise users use VPN s to encrypt transmitted content to protect communication privacy. However, the operators and CSPs(Carrier Service Provider) are interested in their subscribers who used VoIP-Over- Vpntechnology, since it will result in their huge revenue loss while the subscribers escaped the high voice charging. To solve this problem, this paper develops a mechanism to detect and mitigate the VOIP-over- VPN traffic to protect the revenue for the telecommunication industry. In this paper, an advanced packet matching engine is introduced to extract traffic packet features and flow features from encrypted VOIP traffic, and input them into an intelligent detection engine based on heuristic algorithm to identify and classify voIP-over- VPN traffic. Based on the identification and classification results, an Action engine is introduced to block, shape, charge or report the event records. Through plenty of experiments and practices, the VOIP-over-VPN detection and mitigation solution proposed in this paper can achieve more than 95% detection accuracy, and can be alleviated according to different mitigation policies.\",\"PeriodicalId\":391964,\"journal\":{\"name\":\"2022 8th International Conference on Information Management (ICIM)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 8th International Conference on Information Management (ICIM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIM56520.2022.00019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 8th International Conference on Information Management (ICIM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIM56520.2022.00019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
随着IP技术的发展,VoIP(Voice over IP)业务成为目前世界上最流行的语音通信方式。同时,越来越多的个人和企业用户使用VPN对传输的内容进行加密,以保护通信隐私。然而,运营商和运营商服务提供商(csp)对使用VoIP-Over- Vpntechnology的用户很感兴趣,因为这将导致他们的巨大收入损失,而用户却逃避了高昂的话费。为了解决这一问题,本文开发了一种检测和缓解VOIP-over- VPN流量的机制,以保护电信行业的收入。本文引入了一种先进的数据包匹配引擎,从加密的VOIP流量中提取流量数据包特征和流量特征,并将其输入到基于启发式算法的智能检测引擎中,对VOIP -over- VPN流量进行识别和分类。基于识别和分类结果,引入Action引擎对事件记录进行拦截、格式化、收费或报告。通过大量的实验和实践,本文提出的VOIP-over-VPN检测和缓解方案可以达到95%以上的检测准确率,并且可以根据不同的缓解策略进行缓解。
Research on Voip-Over- Vpn s Classification And Mitigation
With the development of IP technology, VoIP(Voice over IP) service is the most popular voice communication mode in the world. At the same time, more and more individual and enterprise users use VPN s to encrypt transmitted content to protect communication privacy. However, the operators and CSPs(Carrier Service Provider) are interested in their subscribers who used VoIP-Over- Vpntechnology, since it will result in their huge revenue loss while the subscribers escaped the high voice charging. To solve this problem, this paper develops a mechanism to detect and mitigate the VOIP-over- VPN traffic to protect the revenue for the telecommunication industry. In this paper, an advanced packet matching engine is introduced to extract traffic packet features and flow features from encrypted VOIP traffic, and input them into an intelligent detection engine based on heuristic algorithm to identify and classify voIP-over- VPN traffic. Based on the identification and classification results, an Action engine is introduced to block, shape, charge or report the event records. Through plenty of experiments and practices, the VOIP-over-VPN detection and mitigation solution proposed in this paper can achieve more than 95% detection accuracy, and can be alleviated according to different mitigation policies.