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Anomaly Detection: A Survey

机译：异常检测：调查

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摘要

Anomaly detection is an important problem that has been researched within diverse research areas and application domains. Many anomaly detection techniques have been specifically developed for certain application domains, while others are more generic. This survey tries to provide a structured and comprehensive overview of the research on anomaly detection. We have grouped existing techniques into different categories based on the underlying approach adopted by each technique. For each category we have identified key assumptions, which are used by the techniques to differentiate between normal and anomalous behavior. When applying a given technique to a particular domain, these assumptions can be used as guidelines to assess the effectiveness of the technique in that domain. For each category, we provide a basic anomaly detection technique, and then show how the different existing techniques in that category are variants of the basic technique. This template provides an easier and more succinct understanding of the techniques belonging to each category. Further, for each category, we identify the advantages and disadvantages of the techniques in that category. We also provide a discussion on the computational complexity of the techniques since it is an important issue in real application domains. We hope that this survey will provide a better understanding of the different directions in which research has been done on this topic, and how techniques developed in one area can be applied in domains for which they were not intended to begin with.
机译：异常检测是已经在不同研究领域和应用领域中研究的重要问题。已经针对某些应用领域专门开发了许多异常检测技术，而其他的则更为通用。本调查试图提供有关异常检测研究的结构化和全面的概述。我们根据每种技术采用的基本方法将现有技术分为不同的类别。对于每种类别，我们都确定了关键假设，这些假设被技术用来区分正常行为和异常行为。当将给定技术应用于特定领域时，这些假设可以用作评估该技术在该领域中有效性的指南。对于每个类别，我们提供一种基本的异常检测技术，然后说明该类别中不同的现有技术如何成为基本技术的变体。该模板提供了对属于每个类别的技术的更轻松，更简洁的理解。此外，对于每个类别，我们将确定该类别中技术的优缺点。我们还讨论了这些技术的计算复杂性，因为它是实际应用程序领域中的重要问题。我们希望这项调查能够更好地理解针对该主题进行研究的不同方向，以及如何将一个领域中开发的技术应用于不打算作为其领域的领域。

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