We establish that during the execution of any Guessing Random Additive Noise Decoding (GRAND) algorithm, an interpretable, useful measure of decoding confidence can be evaluated. This measure takes the form of a log-likelihood ratio (LLR) of the hypotheses that, should a decoding be found by a given query, the decoding is correct versus its being incorrect. That LLR can be used as soft output for a range of applications and we demonstrate its utility by showing that it can be used to confidently discard likely erroneous decodings in favor of returning more readily managed erasures. We show that feature can be used to compromise the physical layer security of short length wiretap codes by accurately and confidently revealing a proportion of a communication when code-rate is far above the Shannon capacity of the associated hard detection channel.

翻译：我们证明，在任意猜测随机加性噪声解码（GRAND）算法的执行过程中，可以评估出一种可解释且有用的解码置信度度量。该度量以假设的对数似然比（LLR）形式呈现，这些假设涉及：若通过给定查询找到解码结果，则该解码正确与不正确的可能性。该LLR可作为软输出用于多种应用，我们通过展示其能够可靠地丢弃可能错误的解码结果，转而返回更易于管理的擦除信号，来证明其实用性。我们进一步表明，这一特性可用于破坏短长度窃听码的物理层安全性——当码率远高于关联硬检测信道的香农容量时，能够准确且可靠地泄露通信内容的一部分。