Ramotsoela, DAbu-Mahfouz, Adnan MIHancke, GP2019-01-162019-01-162018-08Ramotsoela, D., Abu-Mahfouz, A.M.I. and Hancke, G.P. 2018. A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study. Sensors, vol. 18(8): doi:10.3390/s180824911424-8220https://doi.org/10.3390/s18082491https://www.mdpi.com/1424-8220/18/8/2491http://hdl.handle.net/10204/10617This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).The increased use of IndustrialWireless 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.enIndustrial informaticsIndustrial sensor networkCyber-physical systemsCritical infrastructureWater monitoringArticleRamotsoela, D., Abu-Mahfouz, A. M., & Hancke, G. (2018). A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study. http://hdl.handle.net/10204/10617Ramotsoela, D, Adnan MI Abu-Mahfouz, and GP Hancke "A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study." (2018) http://hdl.handle.net/10204/10617Ramotsoela D, Abu-Mahfouz AM, Hancke G. A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study. 2018; http://hdl.handle.net/10204/10617.TY - Article AU - Ramotsoela, D AU - Abu-Mahfouz, Adnan MI AU - Hancke, GP AB - The increased use of IndustrialWireless 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. DA - 2018-08 DB - ResearchSpace DP - CSIR KW - Industrial informatics KW - Industrial sensor network KW - Cyber-physical systems KW - Critical infrastructure KW - Water monitoring LK - https://researchspace.csir.co.za PY - 2018 SM - 1424-8220 T1 - A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study TI - A survey of anomaly detection in Industrial Wireless Sensor Networks with critical water system infrastructure as a case study UR - http://hdl.handle.net/10204/10617 ER -