Hongda Li, Fuqiang Zhang, Lu Yu, Jon Oakley, Hongxin Hu, R. Brooks
{"title":"Towards Efficient Traffic Monitoring for Science DMZ with Side-Channel based Traffic Winnowing","authors":"Hongda Li, Fuqiang Zhang, Lu Yu, Jon Oakley, Hongxin Hu, R. Brooks","doi":"10.1145/3180465.3180474","DOIUrl":null,"url":null,"abstract":"As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.","PeriodicalId":20513,"journal":{"name":"Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization","volume":"23 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2018 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3180465.3180474","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ.