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A Survey of Anomaly Detection in Industrial Wireless Sensor Networks with Critical Water System Infrastructure as a Case Study

机译:以关键供水系统基础设施为例的工业无线传感器网络异常检测调查

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摘要

The increased use of Industrial Wireless Sensor Networks (IWSN) in a variety of different applications, including those that involve critical infrastructure, has meant that adequately protecting these systems has become a necessity. These cyber-physical systems improve the monitoring and control features of these systems but also introduce several security challenges. Intrusion detection is a convenient second line of defence in case of the failure of normal network security protocols. Anomaly detection is a branch of intrusion detection that is resource friendly and provides broader detection generality making it ideal for IWSN applications. These schemes can be used to detect abnormal changes in the environment where IWSNs are deployed. This paper presents a literature survey of the work done in the field in recent years focusing primarily on machine learning techniques. Major research gaps regarding the practical feasibility of these schemes are also identified from surveyed work and critical water infrastructure is discussed as a use case.
机译:工业无线传感器网络(IWSN)在各种不同的应用中(包括涉及关键基础设施的应用)的使用日益增加,这意味着有必要对这些系统进行充分的保护。这些网络物理系统改善了这些系统的监视和控制功能,但同时也带来了一些安全挑战。在正常的网络安全协议失败的情况下,入侵检测是方便的第二道防线。异常检测是入侵检测的一个分支,它是资源友好的并且提供更广泛的检测通用性,使其非常适合IWSN应用程序。这些方案可用于检测部署IWSN的环境中的异常更改。本文对近年来在该领域所做的工作进行了文献综述,主要侧重于机器学习技术。还从调查工作中发现了有关这些方案的实际可行性的主要研究空白,并讨论了关键用水基础设施作为用例。

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