Prognosis: closed-box analysis of network protocol implementations
Prognosis: closed-box analysis of network protocol implementations
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预测：网络协议实现的闭箱分析
DOI：
10.1145/3452296.3472938
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发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Alexandra Silva
中科院分区：
文献类型：
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作者：
Tiago Ferreira;Harrison Brewton;Loris D'antoni;Alexandra Silva
我们提出了一个提供自动封闭盒学习和网络协议实现模型分析的框架。预后可以学习在抽象级别上变化的模型，从简单的确定性自动机到包含数据操作的模型，例如寄存器更新，并且可以用于解锁各种分析技术——模型检查时间属性，计算相同协议的两个实现的模型之间的差异，或者通过基于模型的测试生成来改进测试。预后是模块化的，很容易适应不同的协议（如TCP和QUIC）及其实现。我们使用预后来学习三种QUIC实现（Quiche (Cloudflare)，谷歌QUIC和Facebook mvfst）的模型（部分），并使用这些模型来分析各种实现之间的差异。我们的分析提供了对不同设计选择的见解，并揭示了潜在的缺陷。具体地说，我们在多个QUIC实现中发现了严重的错误，这些错误已经被开发人员承认。
We present Prognosis, a framework offering automated closed-box learning and analysis of models of network protocol implementations. Prognosis can learn models that vary in abstraction level from simple deterministic automata to models containing data operations, such as register updates, and can be used to unlock a variety of analysis techniques -- model checking temporal properties, computing differences between models of two implementations of the same protocol, or improving testing via model-based test generation. Prognosis is modular and easily adaptable to different protocols (e.g. TCP and QUIC) and their implementations. We use Prognosis to learn models of (parts of) three QUIC implementations -- Quiche (Cloudflare), Google QUIC, and Facebook mvfst -- and use these models to analyse the differences between the various implementations. Our analysis provides insights into different design choices and uncovers potential bugs. Concretely, we have found critical bugs in multiple QUIC implementations, which have been acknowledged by the developers.
IETF QUIC 记录层的安全模型和经过充分验证的实现
DOI：
--
发表时间：
2021
期刊：
Proceedings of the IEEE Symposium on Security and Privacy
影响因子：
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作者：
Delignat-Lavaud, Antoine;Fournet, Cédric;Parno, Bryan;Protzenko, Jonathan;Ramananandro, Tahina;Bosamiya, Jay;Lallemand, Joseph;Rakotonirina, Itsaka;Zhou, Yi
通讯作者：
Zhou, Yi