论文标题
关于可解释异常检测的调查
A Survey on Explainable Anomaly Detection
论文作者
论文摘要
在过去的二十年中，大多数关于异常检测的研究都集中在提高检测的准确性上，同时在很大程度上忽略了相应方法的解释性，因此将结果解释留给了从业者。随着异常检测算法越来越多地用于安全 - 关键领域，为这些领域中的高风险决策提供了解释已成为一种道德和监管要求。因此，这项工作提供了有关最先进的可解释异常检测技术的全面和结构化的调查。我们根据主要方面的分类法提出了一种分类学，该分类法表征了每种可解释的异常检测技术，旨在帮助从业人员和研究人员找到最适合其需求的可解释的异常检测方法。
In the past two decades, most research on anomaly detection has focused on improving the accuracy of the detection, while largely ignoring the explainability of the corresponding methods and thus leaving the explanation of outcomes to practitioners. As anomaly detection algorithms are increasingly used in safety-critical domains, providing explanations for the high-stakes decisions made in those domains has become an ethical and regulatory requirement. Therefore, this work provides a comprehensive and structured survey on state-of-the-art explainable anomaly detection techniques. We propose a taxonomy based on the main aspects that characterize each explainable anomaly detection technique, aiming to help practitioners and researchers find the explainable anomaly detection method that best suits their needs.
