Extended Model of Side-Information in Garbling

Tommi Meskanen, Valtteri Niemi, Noora Nieminen
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Abstract

Increasingly many applications utilize network-based solutions these days, such as cloud computing or Internet of Things technologies. Processing private data in various applications over the Internet raises concerns about the user privacy. These concerns may be solved by using novel cryptographic methods, of which garbling schemes is one. Side-information is a key concept for defining the security of garbling schemes since it tells what is allowed to be leaked about the garbled evaluation. Current definitions have a full support to logic circuits while the concept of a garbling scheme should encompass all garbling techniques independent of the model of computation. In this paper, we improve the definition of side-information to fit any computation model, especially Turing machines. Moreover, we show that our definition of side-information also describes better the various threats against the security of garbling schemes, including possible side-channel attacks. We also demonstrate that the new definition has also the following advantages compared to the existing definitions. Our model of side-information supports a wider set of applications, including partial garbling schemes. Our model simplifies the security definitions of garbling schemes without compromising the existing results about the security relations of garbling schemes.
乱码中边信息的扩展模型
如今,越来越多的应用程序利用基于网络的解决方案,例如云计算或物联网技术。在互联网上的各种应用程序中处理私人数据引起了对用户隐私的关注。这些问题可以通过使用新的密码方法来解决,其中乱码方案就是其中之一。侧信息是定义乱码方案安全性的关键概念,因为它告诉我们关于乱码求值的哪些信息是允许泄露的。目前的定义已经完全支持逻辑电路,而一个乱码方案的概念应该包括所有与计算模型无关的乱码技术。在本文中,我们改进了边信息的定义,以适应任何计算模型,特别是图灵机。此外,我们还证明了我们的侧信息定义也更好地描述了针对乱码方案安全性的各种威胁,包括可能的侧信道攻击。我们还证明,与现有定义相比,新定义还具有以下优点。我们的侧信息模型支持更广泛的应用程序集,包括部分乱码方案。我们的模型在不影响现有的关于乱码方案安全关系的结果的前提下,简化了乱码方案的安全定义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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