Abstract
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.
Highlights
Industrial wireless sensor networks (IWSN) have gained popularity in recent years and are being used in a variety of different applications [1,2,3,4,5]
This paper focuses on these two categorisation because they focus on information designers need to have about the data before they can use the algorithm which, as will be explained later, is paramount in anomaly detection schemes
The non-parametric methods are better suited for IWSNs because they are generally more robust but this comes at the cost of a higher computational overhead
Summary
Industrial wireless sensor networks (IWSN) have gained popularity in recent years and are being used in a variety of different applications [1,2,3,4,5]. One of their most important applications involves critical infrastructure, where they form part of supervisory control and data acquisition (SCADA). They are popular in these systems because they provided the same control features as their wired counterparts but have a much lower deployment and maintenance cost These systems introduce the potential for intelligent monitoring and control within the Internet of Things (IoT) application environment. In the application domain these networks are usually deployed in hostile environments and their resource constraints introduce several security challenges [9,10,11,12]
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