Hang Huang;Honglei Wang;Jia Rao;Song Wu;Hao Fan;Chen Yu;Hai Jin;Kun Suo;Lisong Pan
{"title":"vKernel:通过私有代码和数据加强容器隔离","authors":"Hang Huang;Honglei Wang;Jia Rao;Song Wu;Hao Fan;Chen Yu;Hai Jin;Kun Suo;Lisong Pan","doi":"10.1109/TC.2024.3383988","DOIUrl":null,"url":null,"abstract":"Container technology is increasingly adopted in cloud environments. However, the lack of isolation in the shared kernel becomes a significant barrier to the wide adoption of containers. The challenges lie in how to simultaneously attain high performance and isolation. On the one hand, kernel-level isolation mechanisms, such as \n<italic>seccomp</i>\n, \n<italic>capabilities</i>\n, and \n<italic>apparmor</i>\n, achieve good performance without much overhead, but lack the support for per-container customization. On the other hand, user-level and VM-based isolation offer superior security guarantees and allow for customization, since a container is assigned a dedicated kernel, but at the cost of high overhead. We present vKernel, a kernel isolation framework. It maintains a minimal set of code and data that are either sensitive or prone to interference in a \n<italic>vKernel Instance</i>\n (vKI). vKernel relies on inline hooks to intercept and redirect requests sent to the host kernel to a vKI, where container-specific security rules, functions, and data are implemented. Through case studies, we demonstrate that under vKernel user-defined data isolation and kernel customization can be supported with a reasonable engineering effort. An evaluation of vKernel with micro-benchmarks, cloud services, real-world applications show that vKernel achieves good security guarantees, but with much less overhead.","PeriodicalId":13087,"journal":{"name":"IEEE Transactions on Computers","volume":"73 7","pages":"1711-1723"},"PeriodicalIF":3.6000,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10494778","citationCount":"0","resultStr":"{\"title\":\"vKernel: Enhancing Container Isolation via Private Code and Data\",\"authors\":\"Hang Huang;Honglei Wang;Jia Rao;Song Wu;Hao Fan;Chen Yu;Hai Jin;Kun Suo;Lisong Pan\",\"doi\":\"10.1109/TC.2024.3383988\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Container technology is increasingly adopted in cloud environments. However, the lack of isolation in the shared kernel becomes a significant barrier to the wide adoption of containers. The challenges lie in how to simultaneously attain high performance and isolation. On the one hand, kernel-level isolation mechanisms, such as \\n<italic>seccomp</i>\\n, \\n<italic>capabilities</i>\\n, and \\n<italic>apparmor</i>\\n, achieve good performance without much overhead, but lack the support for per-container customization. On the other hand, user-level and VM-based isolation offer superior security guarantees and allow for customization, since a container is assigned a dedicated kernel, but at the cost of high overhead. We present vKernel, a kernel isolation framework. It maintains a minimal set of code and data that are either sensitive or prone to interference in a \\n<italic>vKernel Instance</i>\\n (vKI). vKernel relies on inline hooks to intercept and redirect requests sent to the host kernel to a vKI, where container-specific security rules, functions, and data are implemented. Through case studies, we demonstrate that under vKernel user-defined data isolation and kernel customization can be supported with a reasonable engineering effort. An evaluation of vKernel with micro-benchmarks, cloud services, real-world applications show that vKernel achieves good security guarantees, but with much less overhead.\",\"PeriodicalId\":13087,\"journal\":{\"name\":\"IEEE Transactions on Computers\",\"volume\":\"73 7\",\"pages\":\"1711-1723\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10494778\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Transactions on Computers\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10494778/\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Computers","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10494778/","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, HARDWARE & ARCHITECTURE","Score":null,"Total":0}
vKernel: Enhancing Container Isolation via Private Code and Data
Container technology is increasingly adopted in cloud environments. However, the lack of isolation in the shared kernel becomes a significant barrier to the wide adoption of containers. The challenges lie in how to simultaneously attain high performance and isolation. On the one hand, kernel-level isolation mechanisms, such as
seccomp
,
capabilities
, and
apparmor
, achieve good performance without much overhead, but lack the support for per-container customization. On the other hand, user-level and VM-based isolation offer superior security guarantees and allow for customization, since a container is assigned a dedicated kernel, but at the cost of high overhead. We present vKernel, a kernel isolation framework. It maintains a minimal set of code and data that are either sensitive or prone to interference in a
vKernel Instance
(vKI). vKernel relies on inline hooks to intercept and redirect requests sent to the host kernel to a vKI, where container-specific security rules, functions, and data are implemented. Through case studies, we demonstrate that under vKernel user-defined data isolation and kernel customization can be supported with a reasonable engineering effort. An evaluation of vKernel with micro-benchmarks, cloud services, real-world applications show that vKernel achieves good security guarantees, but with much less overhead.
期刊介绍:
The IEEE Transactions on Computers is a monthly publication with a wide distribution to researchers, developers, technical managers, and educators in the computer field. It publishes papers on research in areas of current interest to the readers. These areas include, but are not limited to, the following: a) computer organizations and architectures; b) operating systems, software systems, and communication protocols; c) real-time systems and embedded systems; d) digital devices, computer components, and interconnection networks; e) specification, design, prototyping, and testing methods and tools; f) performance, fault tolerance, reliability, security, and testability; g) case studies and experimental and theoretical evaluations; and h) new and important applications and trends.