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P2 Discovering ePassport Vulnerabilities using Bisimilarity

使用互模拟发现电子护照(ePassport)漏洞
LMCS vol.Volume 17, Issue 22021匹配度 2/10 · 该论文属于形式化方法与安全协议验证,使用互模拟和模态逻辑分析电子护照隐私漏洞,与用户核心方向(LLM 与静态分析/形式化验证交叉、浮点程序分析、贝叶斯程序分析)没有直接交集;仅在“形式化验证”这一宽泛标签上相关。引用 1 inbox
Ross Horne, Sjouke Mauw
crossref: 2026-09-10

AI 速览

一句话:用开放互模拟与经典FM模态逻辑发现并证明电子护照BAC/PACE协议的可链接性隐私漏洞。

本文揭示全球电子护照所实现的 ICAO 9303 标准中的隐私漏洞:近期通过检查站的持照人可在不打开电子护照的情况下被重新识别。作者以互模拟(bisimilarity)为核心分析工具,针对 applied π-calculus 提出一链方法:符号欠近似的开放互模拟(open bisimilarity),以及用于描述和证明攻击的经典 FM 模态逻辑。该漏洞利用 BAC 认证协议,并对改进安全性的 PACE 协议仍然有效,且已获 ICAO 确认。论文还给出证据,论证一种更准确反映攻击者能力的不可链接性(unlinkability)规约方案。

问题
电子护照 ICAO 9303 的 BAC/PACE 认证协议是否存在可被利用的隐私漏洞,使持照人通过检查站后被重新识别,即破坏不可链接性(unlinkability)。
方法
使用 applied π-calculus 建模协议,发展开放互模拟作为符号欠近似,并引入经典 FM 模态逻辑来描述和证明攻击;同时提出新的 unlinkability 规约方案。
评估
以互模拟分析发现 BAC 漏洞并证明其对 PACE 仍有效,漏洞获 ICAO 确认;并通过案例论证新规约方案更准确反映攻击者能力。
原文摘要(Abstract)

We uncover privacy vulnerabilities in the ICAO 9303 standard implemented by ePassports worldwide. These vulnerabilities, confirmed by ICAO, enable an ePassport holder who recently passed through a checkpoint to be reidentified without opening their ePassport. This paper explains how bisimilarity was used to discover these vulnerabilities, which exploit the BAC protocol - the original ICAO 9303 standard ePassport authentication protocol - and remains valid for the PACE protocol, which improves on the security of BAC in the latest ICAO 9303 standards. In order to tackle such bisimilarity problems, we develop here a chain of methods for the applied $\pi$-calculus including a symbolic under-approximation of bisimilarity, called open bisimilarity, and a modal logic, called classical FM, for describing and certifying attacks. Evidence is provided to argue for a new scheme for specifying such unlinkability problems that more accurately reflects the capabilities of an attacker.

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BibTeX
@article{paperbot1304,
  title = {Discovering ePassport Vulnerabilities using Bisimilarity},
  author = {Ross Horne and Sjouke Mauw},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 17, Issue 2},
  year = {2021},
  doi = {10.23638/lmcs-17(2:24)2021}
}