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：我们确认,在执行任何猜想随机添加噪声解码算法(GRAND)期间,可以对一种可解释的、有用的解码信任度进行评估。这一计量法采取的一种假设形式是,如果某个查询找到解码,解码是正确的,而不是不正确的。LLLR可以用作一系列应用的软输出,我们通过显示它可以被利用来自信地丢弃可能错误的解码,以利返回更便于管理的破译。作为应用,我们表明,在代码率超过容量时,可以使用特征准确和自信地披露通信的一部分,从而损害短线码的物理层安全。