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. As an application, 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 above capacity.

翻译：我们证明，在执行任何猜测随机加性噪声解码（GRAND）算法过程中，可以评估一种可解释、有用的解码置信度度量。该度量采用似然比（LLR）的形式，表示在给定查询下找到的解码正确的假设与错误的假设之间的比值。该LLR可作为软输出应用于多种场景，我们通过展示其可被用于自信地丢弃可能错误的解码结果，转而返回更易处理的擦除信号，验证了其效用。作为应用实例，我们表明该特性可通过在码率高于容量时准确且自信地泄露部分通信内容，从而破坏短长度窃听码的物理层安全性。