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Breaking MPC implementations through compression

机译:通过压缩打破MPC实现

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摘要

There are many cryptographic protocols in the literature that are scientifically and mathematically sound. By extension, cryptography today seeks to respond to numerous properties of the communication process beyond confidentiality (secrecy), such as integrity, authenticity, and anonymity. In addition to the theoretical evidence, implementations must be equally secure. Due to the ever-increasing intrusion from governments and other groups, citizens are now seeking alternatives ways of communication that do not leak information. In this paper, we analyze multiparty computation (MPC), which is a sub-field of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. This is a very useful method that can be used, for example, to carry out computations on anonymous data without having to leak that data. Thus, due to the importance of confidentiality in this type of technique, we analyze active and passive attacks using complexity measures (compression and entropy). We start by obtaining network traces and syscalls, then we analyze them using compression and entropy techniques. Finally, we cluster the traces and syscalls using standard clustering techniques. This approach does not need any deep specific knowledge of the implementations being analyzed. This paper presents a security analysis for four MPC frameworks, where three were identified as insecure. These insecure libraries leak information about the inputs provided by each party of the communication. Additionally, we have detected, through a careful analysis of its source code, that SPDZ-2's secret sharing schema always produces the same results.
机译:文献中有许多加密协议在科学和数学上的声音。通过扩展,加密今天寻求响应许多超越机密性(保密)的众多属性,例如完整性,真实性和匿名性。除了理论证据外,实施必须同样安全。由于各国政府和其他群体的侵扰,公民正在寻求替代沟通方式,这些沟通方式不会泄漏信息。在本文中,我们分析了多分算计算(MPC),这是一个密码学的子场,其目标是创建各方的方法,以在保持这些输入私有的同时在其输入上共同计算函数。这是一种非常有用的方法,例如,可以使用,例如,在不必泄漏该数据的情况下对匿名数据进行计算。因此,由于在这种类型的技术中保密的重要性,我们使用复杂度措施(压缩和熵)分析主动和被动攻击。我们首先获取网络迹线和Syscalls,然后我们使用压缩和熵技术分析它们。最后,我们使用标准聚类技术培养迹线和Syscalls。这种方法不需要对正在分析的实现的任何深刻的具体知识。本文提出了四个MPC框架的安全分析,其中三个被识别为不安全。这些不安全的库泄露有关每方通信提供的输入的信息。此外,我们通过仔细分析其源代码来检测,SPDZ-2的秘密共享模式始终产生相同的结果。

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