Measuring Anonymity with Plausibilistic Entropy

I. Goriac
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引用次数: 3

Abstract

To prove that a certain protocol provides a certain security property (e.g. anonymity) one must first formally define that property in the context of a logical framework capable of expressing the relevant aspects of that protocol and then perform the actual inference steps (preferably automatically). After the qualitative aspect of the property is successfully addressed the next issue is the strength of the property - how to express it quantitatively so that it can be compared both to some business requirements and to other implementing protocols. The framework that we build upon is the MAS epistemic logic introduced by Halpern and O'Neill in their approach for defining anonymity both possibilistically and probabilistically. Our contribution employs the highly general plausibilistic approach in order to provide a numeric measure for anonymity that can also be extended to other properties as well. We propose a formula for calculating a particular kind of entropy suited for characterising partially ordered sets used to define plausibility measures and, on top of it, a quantitative definition for anonymity. We believe that the theory presented here is capable of filling the gap between the very general qualitative definition of anonymity and the information intensive probabilistic approach that might not always be applicable.
用似然熵测量匿名性
为了证明某个协议提供了某个安全属性(例如匿名性),必须首先在能够表达该协议相关方面的逻辑框架上下文中正式定义该属性,然后执行实际的推理步骤(最好是自动的)。在成功地解决了属性的定性方面之后,下一个问题是属性的强度——如何定量地表达它,以便可以将其与某些业务需求和其他实现协议进行比较。我们建立的框架是由Halpern和O'Neill在他们的方法中引入的MAS认知逻辑,用于从可能性和概率上定义匿名。我们的贡献采用了高度通用的似是而非的方法,以便为匿名性提供一个数字度量,也可以扩展到其他属性。我们提出了一个公式来计算一种特定的熵,它适合于描述用于定义合理性度量的部分有序集合的特征,并在此基础上给出了匿名性的定量定义。我们认为,这里提出的理论能够填补匿名性的非常一般的定性定义和信息密集的概率方法之间的差距,这可能并不总是适用的。
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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