• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

黑暗之地的漏锅:理解SGX中的内存侧信道风险

Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX.

作者信息

Wang Wenhao, Chen Guoxing, Pan Xiaorui, Zhang Yinqian, Wang XiaoFeng, Bindschaedler Vincent, Tang Haixu, Gunter Carl A

机构信息

Indiana University, Bloomington,

The Ohio State University,

出版信息

Conf Comput Commun Secur. 2017 Oct-Nov;2017:2421-2434. doi: 10.1145/3133956.3134038.

DOI:10.1145/3133956.3134038
PMID:30853868
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6405214/
Abstract

Side-channel risks of Intel's SGX have recently attracted great attention. Under the spotlight is the newly discovered page-fault attack, in which an OS-level adversary induces page faults to observe the page-level access patterns of a protected process running in an SGX enclave. With almost all proposed defense focusing on this attack, little is known about whether such efforts indeed raises the bar for the adversary, whether a simple variation of the attack renders all protection ineffective, not to mention an in-depth understanding of other attack surfaces in the SGX system. In the paper, we report the first step toward systematic analyses of side-channel threats that SGX faces, focusing on the risks associated with its memory management. Our research identifies 8 potential attack vectors, ranging from TLB to DRAM modules. More importantly, we highlight the common misunderstandings about SGX memory side channels, demonstrating that high frequent AEXs can be avoided when recovering EdDSA secret key through a new page channel and fine-grained monitoring of enclave programs (at the level of 64B) can be done through combining both cache and cross-enclave DRAM channels. Our findings reveal the gap between the ongoing security research on SGX and its side-channel weaknesses, redefine the side-channel threat model for secure enclaves, and can provoke a discussion on when to use such a system and how to use it securely.

摘要

英特尔软件防护扩展(SGX)的侧信道风险最近备受关注。其中备受瞩目的是新发现的页面错误攻击,在这种攻击中,操作系统级别的对手会引发页面错误,以观察在SGX飞地中运行的受保护进程的页面级访问模式。几乎所有提出的防御措施都聚焦于这种攻击,对于这些努力是否真的提高了对手的攻击门槛、攻击的简单变体是否会使所有保护措施失效,我们知之甚少,更不用说对SGX系统中其他攻击面的深入理解了。在本文中,我们报告了对SGX面临的侧信道威胁进行系统分析的第一步,重点关注与其内存管理相关的风险。我们的研究确定了8个潜在的攻击向量,范围从转换后备缓冲器(TLB)到动态随机存取存储器(DRAM)模块。更重要的是,我们强调了对SGX内存侧信道的常见误解,表明通过一个新的页面信道恢复EdDSA秘密密钥时可以避免高频率的异步外部中断(AEX),并且通过结合缓存和跨飞地DRAM信道,可以对飞地程序进行细粒度监控(在64字节级别)。我们的发现揭示了当前关于SGX的安全研究与其侧信道弱点之间的差距,重新定义了安全飞地的侧信道威胁模型,并可能引发关于何时使用这样的系统以及如何安全使用它的讨论。

相似文献

1
Leaky Cauldron on the Dark Land: Understanding Memory Side-Channel Hazards in SGX.黑暗之地的漏锅:理解SGX中的内存侧信道风险
Conf Comput Commun Secur. 2017 Oct-Nov;2017:2421-2434. doi: 10.1145/3133956.3134038.
2
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework.HySec-Flow:基于SGX的大数据分析框架实现隐私保护的基因组计算
IEEE Int Conf Cloud Comput. 2021 Sep;2021:733-743. doi: 10.1109/CLOUD53861.2021.00098. Epub 2021 Nov 13.
3
Trust Beyond Border: Lightweight, Verifiable User Isolation for Protecting In-Enclave Services.超越边界的信任:用于保护飞地内服务的轻量级、可验证的用户隔离
IEEE Trans Dependable Secure Comput. 2023 Jan-Feb;20(1):522-538. doi: 10.1109/tdsc.2021.3138427. Epub 2021 Dec 28.
4
eTPM: A Trusted Cloud Platform Enclave TPM Scheme Based on Intel SGX Technology.eTPM:一种基于 Intel SGX 技术的可信云平台 Enclave TPM 方案。
Sensors (Basel). 2018 Nov 6;18(11):3807. doi: 10.3390/s18113807.
5
PREMIX: PRivacy-preserving EstiMation of Individual admiXture.预混:个体混合比例的隐私保护估计
AMIA Annu Symp Proc. 2017 Feb 10;2016:1747-1755. eCollection 2016.
6
Extracting the Secrets of OpenSSL with RAMBleed.使用 RAMBleed 提取 OpenSSL 的秘密。
Sensors (Basel). 2022 May 9;22(9):3586. doi: 10.3390/s22093586.
7
The Danger of Minimum Exposures: Understanding Cross-App Information Leaks on iOS through Multi-Side-Channel Learning.最小暴露的危险:通过多侧信道学习理解iOS上的跨应用信息泄露
Conf Comput Commun Secur. 2023 Nov;2023:281-295. doi: 10.1145/3576915.3616655. Epub 2023 Nov 21.
8
Practical and Efficient in-Enclave Verification of Privacy Compliance.实用且高效的飞地隐私合规性验证
Proc (Int Conf Dependable Syst Netw). 2021 Jun;2021:413-425. doi: 10.1109/dsn48987.2021.00052. Epub 2021 Aug 6.
9
Important modifications by sugammadex, a modified γ-cyclodextrin, of ion currents in differentiated NSC-34 neuronal cells.环糊精衍生物舒更葡糖钠对分化的NSC-34神经细胞离子电流的重要修饰作用
BMC Neurosci. 2017 Jan 3;18(1):6. doi: 10.1186/s12868-016-0320-5.
10
In-DRAM Cache Management for Low Latency and Low Power 3D-Stacked DRAMs.用于低延迟和低功耗3D堆叠DRAM的片上动态随机存取存储器缓存管理
Micromachines (Basel). 2019 Feb 14;10(2):124. doi: 10.3390/mi10020124.

引用本文的文献

1
Secure and federated genome-wide association studies for biobank-scale datasets.针对生物样本库规模数据集的安全且联合的全基因组关联研究。
Nat Genet. 2025 Apr;57(4):809-814. doi: 10.1038/s41588-025-02109-1. Epub 2025 Feb 24.
2
Trust Beyond Border: Lightweight, Verifiable User Isolation for Protecting In-Enclave Services.超越边界的信任:用于保护飞地内服务的轻量级、可验证的用户隔离
IEEE Trans Dependable Secure Comput. 2023 Jan-Feb;20(1):522-538. doi: 10.1109/tdsc.2021.3138427. Epub 2021 Dec 28.
3
Practical and Efficient in-Enclave Verification of Privacy Compliance.实用且高效的飞地隐私合规性验证
Proc (Int Conf Dependable Syst Netw). 2021 Jun;2021:413-425. doi: 10.1109/dsn48987.2021.00052. Epub 2021 Aug 6.
4
HySec-Flow: Privacy-Preserving Genomic Computing with SGX-based Big-Data Analytics Framework.HySec-Flow:基于SGX的大数据分析框架实现隐私保护的基因组计算
IEEE Int Conf Cloud Comput. 2021 Sep;2021:733-743. doi: 10.1109/CLOUD53861.2021.00098. Epub 2021 Nov 13.
5
Privacy-preserving genotype imputation in a trusted execution environment.在可信执行环境中进行隐私保护的基因型推断。
Cell Syst. 2021 Oct 20;12(10):983-993.e7. doi: 10.1016/j.cels.2021.08.001. Epub 2021 Aug 26.
6
SAFETY: Secure gwAs in Federated Environment through a hYbrid Solution.安全性:通过混合解决方案确保联邦环境中的安全 gwAs。
IEEE/ACM Trans Comput Biol Bioinform. 2019 Jan-Feb;16(1):93-102. doi: 10.1109/TCBB.2018.2829760. Epub 2018 Apr 24.
7
Secure and Efficient Regression Analysis Using a Hybrid Cryptographic Framework: Development and Evaluation.使用混合加密框架的安全高效回归分析:开发与评估
JMIR Med Inform. 2018 Mar 5;6(1):e14. doi: 10.2196/medinform.8286.