{"title":"定时SDN控制平面来推断网络配置","authors":"J. Sonchack, Adam J. Aviv, Eric Keller","doi":"10.1145/2876019.2876030","DOIUrl":null,"url":null,"abstract":"In this paper, we study information leakage by control planes of Software Defined Networks. We find that the response time of an OpenFlow control plane depends on its workload, and we develop an inference attack that an adversary with control of a single host could use to learn about network configurations without needing to compromise any network infrastructure (i.e. switches or controller servers). We also demonstrate that our inference attack works on real OpenFlow hardware. To our knowledge, no previous work has evaluated OpenFlow inference attacks outside of simulation.","PeriodicalId":107409,"journal":{"name":"Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"Timing SDN Control Planes to Infer Network Configurations\",\"authors\":\"J. Sonchack, Adam J. Aviv, Eric Keller\",\"doi\":\"10.1145/2876019.2876030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we study information leakage by control planes of Software Defined Networks. We find that the response time of an OpenFlow control plane depends on its workload, and we develop an inference attack that an adversary with control of a single host could use to learn about network configurations without needing to compromise any network infrastructure (i.e. switches or controller servers). We also demonstrate that our inference attack works on real OpenFlow hardware. To our knowledge, no previous work has evaluated OpenFlow inference attacks outside of simulation.\",\"PeriodicalId\":107409,\"journal\":{\"name\":\"Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2876019.2876030\",\"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 2016 ACM International Workshop on Security in Software Defined Networks & Network Function Virtualization","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2876019.2876030","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Timing SDN Control Planes to Infer Network Configurations
In this paper, we study information leakage by control planes of Software Defined Networks. We find that the response time of an OpenFlow control plane depends on its workload, and we develop an inference attack that an adversary with control of a single host could use to learn about network configurations without needing to compromise any network infrastructure (i.e. switches or controller servers). We also demonstrate that our inference attack works on real OpenFlow hardware. To our knowledge, no previous work has evaluated OpenFlow inference attacks outside of simulation.