Smart Card Research and Advanced Applications - 17th International Conference, CARDIS 2018, Montpellier, France, November 12-14, 2018, Revised Selected Papers
Smart Card Research and Advanced Applications - 17th International Conference, CARDIS 2018, Montpellier, France, November 12-14, 2018, Revised Selected Papers
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智能卡研究和高级应用 - 第 17 届国际会议，CARDIS 2018，法国蒙彼利埃，2018 年 11 月 12-14 日，修订后的精选论文
DOI：
10.1007/978-3-030-15462-2_2
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Green J
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文献类型：
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作者：
Green J
置信传播或和积算法是一种强大且众所周知的概率图模型推理方法，已由Veyrat-Charvillon等人[14]提出用于侧信道分析中的特定用途。我们定义了一种新的度量来捕获因子图中变量节点的重要性，我们针对侧信道分析中的特定用例提出了对和积算法的两种改进，并且我们明确地定义和检查组合来自多个侧信道迹线的信息的不同方式。有了这些新的考虑，我们系统地研究了一些图形模型，“自然”遵循AES的实现。我们的结果出乎意料：更大的图（即更多的边信道信息）和更多的连通性都不一定导致明显更好的攻击。事实上，我们的研究结果表明，在实践中，（总的来说）最好的选择是在独立的图形组合设置中利用非循环图，这使我们能够证明收敛到正确的密钥分布。我们提供的证据使用广泛的模拟和最终的验证性分析真实的跟踪数据。
Belief propagation, or the sum-product algorithm, is a powerful and well known method for inference on probabilistic graphical models, which has been proposed for the specific use in side channel analysis by Veyrat-Charvillon et al. [14].We define a novel metric to capture theimportanceof variable nodes in factor graphs, we propose two improvements to the sum-product algorithm for the specific use case in side channel analysis, and we explicitly define and examine different ways of combining information from multiple side channel traces. With these new considerations we systematically investigate a number of graphical models that “naturally” follow from an implementation of AES. Our results are unexpected: neither a larger graph (i.e. more side channel information) nor more connectedness necessarily lead to significantly better attacks. In fact our results demonstrate that in practice the (on balance) best choice is to utilise an acyclic graph in an independent graph combination setting, which gives us provable convergence to the correct key distribution. We provide evidence using both extensive simulations and a final confirmatory analysis on real trace data.