Optimising Faceted Secure Multi-Execution

Maximilian Algehed, Alejandro Russo, C. Flanagan
{"title":"Optimising Faceted Secure Multi-Execution","authors":"Maximilian Algehed, Alejandro Russo, C. Flanagan","doi":"10.1109/CSF.2019.00008","DOIUrl":null,"url":null,"abstract":"Language-Based Information Flow Control (IFC) provides strong security guarantees for untrusted code, but often suffers from a non-negligible rate of false alarms. Multi-execution based techniques promise to provide security guarantees without raising any false alarms. However, all known multi-execution approaches introduce extraneous performance overheads which are rarely studied. In this work, we lay down the foundations for optimisation techniques aimed at reducing these overheads to a managable level, thus helping to make multi-execution more practical. We characterise our optimisations as data-and control-oriented. Data-oriented optimisations reduce storage overheads— which also helps to remove unnecessary repeated computations. In contrast, computation-oriented optimisations rely on program annotations in order to reduce needless computation. These annotations motivate the need for a new, stronger, theoretical notion of transparency— i.e., a stronger notion for characterising the lack of false alarms. To show the efficacy of our optimisation techniques, we apply them to two case-studies: a secure (faceted) database and a chat server written in a multi-execution based IFC framework. Our case-studies clearly show that our optimisations significantly reduce the storage and computational overhead, sometimes from exponential to polynomial order. All of our formal results are accompanied by mechanised proofs in Agda.","PeriodicalId":249093,"journal":{"name":"2019 IEEE 32nd Computer Security Foundations Symposium (CSF)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE 32nd Computer Security Foundations Symposium (CSF)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSF.2019.00008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

Language-Based Information Flow Control (IFC) provides strong security guarantees for untrusted code, but often suffers from a non-negligible rate of false alarms. Multi-execution based techniques promise to provide security guarantees without raising any false alarms. However, all known multi-execution approaches introduce extraneous performance overheads which are rarely studied. In this work, we lay down the foundations for optimisation techniques aimed at reducing these overheads to a managable level, thus helping to make multi-execution more practical. We characterise our optimisations as data-and control-oriented. Data-oriented optimisations reduce storage overheads— which also helps to remove unnecessary repeated computations. In contrast, computation-oriented optimisations rely on program annotations in order to reduce needless computation. These annotations motivate the need for a new, stronger, theoretical notion of transparency— i.e., a stronger notion for characterising the lack of false alarms. To show the efficacy of our optimisation techniques, we apply them to two case-studies: a secure (faceted) database and a chat server written in a multi-execution based IFC framework. Our case-studies clearly show that our optimisations significantly reduce the storage and computational overhead, sometimes from exponential to polynomial order. All of our formal results are accompanied by mechanised proofs in Agda.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
优化面安全多执行
基于语言的信息流控制(IFC)为不受信任的代码提供了强大的安全保证,但经常遭受不可忽略的假警报率。基于多执行的技术承诺在不引发任何假警报的情况下提供安全保证。然而,所有已知的多执行方法都会引入额外的性能开销,而这些开销很少被研究。在这项工作中,我们为优化技术奠定了基础,旨在将这些开销降低到可管理的水平,从而有助于使多执行更加实用。我们将我们的优化描述为面向数据和控制。面向数据的优化减少了存储开销——这也有助于消除不必要的重复计算。相反,面向计算的优化依赖于程序注释,以减少不必要的计算。这些注释激发了对新的、更强的、理论性的透明度概念的需求——也就是说,对缺乏假警报的特征的更强的概念。为了展示我们的优化技术的有效性,我们将它们应用于两个案例研究:一个安全(分面)数据库和一个基于多执行的IFC框架编写的聊天服务器。我们的案例研究清楚地表明,我们的优化大大减少了存储和计算开销,有时从指数级到多项式级。我们所有的正式结果都伴随着Agda的机械化证明。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Using Information Flow to Design an ISA that Controls Timing Channels Information Flow Control for Distributed Trusted Execution Environments Time-Dependent Decision-Making and Decentralization in Proof-of-Work Cryptocurrencies Prime, Order Please! Revisiting Small Subgroup and Invalid Curve Attacks on Protocols using Diffie-Hellman Formalizing Constructive Cryptography using CryptHOL
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1