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P2 A Benchmark Suite for Evaluating Caches' Vulnerability to Timing Attacks

评估缓存对时序攻击脆弱性的基准测试套件
ASPLOS Proceedings of the Twenty-Fifth International Conference on Architectural Support for Programming Languages and Operating Systems2020匹配度 1/10 · 论文主题是处理器缓存时序攻击的安全基准与CTVS评分,属于硬件安全/体系结构领域,与用户关注的静态分析、LLM/Agent程序分析、浮点程序分析及贝叶斯程序分析等方向无直接关联,也不涉及程序语言或机器学习系统。引用 20 inbox
Shuwen Deng, Wenjie Xiong, Jakub Szefer
crossref: 2026-09-12

AI 速览

一句话:提出覆盖88种强时序漏洞的缓存攻击基准套件,并给出CTVS评分。

论文针对处理器缓存对时序攻击的脆弱性难以统一评估的问题,改进了已有的三步缓存时序攻击模型,系统化地推导出88种“强”理论漏洞。作者实现了一个基准测试套件,自动生成1094个测试程序覆盖这些漏洞,并据此计算缓存时序漏洞分数(CTVS),分数越小表示缓存设计越安全。评估在商用Intel与AMD处理器上进行,表明不同处理器实现会暴露不同类型的攻击,也验证了基准与CTVS可用于仿真,帮助新安全处理器和缓存设计者评估设计对时序攻击的敏感度。

问题
如何系统化地评估不同处理器缓存实现对时序攻击的脆弱性,并比较不同设计的安全性。
方法
改进三步缓存时序攻击模型,推导88种强理论漏洞,自动生成1094个测试程序构成基准套件,并计算CTVS评分。
评估
在商用Intel和AMD处理器上运行基准,比较不同实现易受攻击类型,并说明其可用于仿真中的安全设计评估。
原文摘要(Abstract)

Based on improvements to an existing three-step model for cache timing-based attacks, this work presents 88 Strong types of theoretical timing-based vulnerabilities in processor caches. It also presents and implements a new benchmark suite that can be used to test if processor cache is vulnerable to one of the attacks. In total, there are 1094 automatically-generated test programs which cover the 88 Strong theoretical vulnerabilities. The benchmark suite generates the Cache Timing Vulnerability Score (CTVS) which can be used to evaluate how vulnerable a specific cache implementation is to different attacks. A smaller CTVS means the design is more secure. Evaluation is conducted on commodity Intel and AMD processors and shows how the differences in processor implementations can result in different types of attacks that they are vulnerable to. Further, the benchmarks and the CTVS can be used in simulation to help designers of new secure processors and caches evaluate their designs' susceptibility to cache timing-based attacks.

链接与引用

DOI 原文 · PDF(开放获取) ·

BibTeX
@inproceedings{paperbot5417,
  title = {A Benchmark Suite for Evaluating Caches' Vulnerability to Timing Attacks},
  author = {Shuwen Deng and Wenjie Xiong and Jakub Szefer},
  booktitle = {ASPLOS},
  year = {2020},
  doi = {10.1145/3373376.3378510}
}