Ongoing research on anomaly detection for the Internet of Things (IoT) is a rapidly expanding field. This growth necessitates an examination of application trends and current gaps. The vast majority of those publications are in areas such as network and infrastructure security, sensor monitoring, smart home, and smart city applications and are extending into even more sectors. Recent advancements in the field have increased the necessity to study the many IoT anomaly detection applications. This paper begins with a summary of the detection methods and applications, accompanied by a discussion of the categorization of IoT anomaly detection algorithms. We then discuss the current publications to identify distinct application domains, examining papers chosen based on our search criteria. The survey considers 64 papers among recent publications published between January 2019 and July 2021. In recent publications, we observed a shortage of IoT anomaly detection methodologies, for example, when dealing with the integration of systems with various sensors, data and concept drifts, and data augmentation where there is a shortage of Ground Truth data. Finally, we discuss the present such challenges and offer new perspectives where further research is required.
翻译:对物联网异常现象的不断研究是一个迅速扩大的领域,这一增长需要研究应用趋势和目前的差距,这些出版物绝大多数是在网络和基础设施安全、传感器监测、智能家庭、智能城市应用和智能城市应用等领域,并正在扩展到更多的部门。最近实地的进展增加了研究许多IoT异常现象检测应用的必要性。本文件首先概述探测方法和应用,并同时讨论IoT异常现象检测算法的分类。然后我们讨论目前的出版物,以查明不同的应用领域,审查根据我们的搜索标准选择的文件。调查将64篇论文纳入2019年1月至2021年7月出版的近期出版物中。在最近的出版物中,我们发现IoT异常现象检测方法短缺,例如,在将系统与各种传感器、数据和概念漂移相结合时,以及在缺少地面真相数据的地方,数据增强数据。最后,我们讨论目前的挑战,并提出需要进一步研究的新观点。