Scipediacontent: Scipediacontent moved page Draft Content 526443912 to Hindy et al 2019a

2020-10-14T14:38:03Z

Scipediacontent moved page Draft Content 526443912 to Hindy et al 2019a

Scipediacontent: Created page with " == Abstract == Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex proce..."

2020-10-14T14:37:59Z

Created page with " == Abstract == Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex proce..."

New page

== Abstract ==

Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex process and communication of those systems. Supervisory control and data acquisition (SCADA) systems are used in industrial, infrastructure and facility processes (e.g. manufacturing, fabrication, oil and water pipelines, building ventilation, etc.) Like other Internet of Things (IoT) implementations, SCADA systems are vulnerable to cyber-attacks, therefore, a robust anomaly detection is a major requirement. However, having an accurate anomaly detection system is not an easy task, due to the difficulty to differentiate between cyber-attacks and system internal failures (e.g. hardware failures). In this paper, we present a model that detects anomaly events in a water system controlled by SCADA. Six Machine Learning techniques have been used in building and evaluating the model. The model classifies different anomaly events including hardware failures (e.g. sensor failures), sabotage and cyber-attacks (e.g. DoS and Spoofing). Unlike other detection systems, our proposed work focuses on notifying the operator when an anomaly occurs with a probability of the event occurring. This additional information helps in accelerating the mitigation process. The model is trained and tested using a real-world dataset.

Document type: Part of book or chapter of book

== Full document ==
<pdf>Media:Draft_Content_526443912-beopen1058-3640-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://arxiv.org/abs/1904.05724 http://arxiv.org/abs/1904.05724]

* [http://arxiv.org/pdf/1904.05724 http://arxiv.org/pdf/1904.05724]

* [http://dx.doi.org/10.1007/978-3-030-12786-2_1 http://dx.doi.org/10.1007/978-3-030-12786-2_1]

* [http://hdl.handle.net/10985/15039 http://hdl.handle.net/10985/15039]

* [https://strathprints.strath.ac.uk/70936/1/Hindy_etal_CyberICPS2018_Improving_SIEM_for_critical_SCADA_water_infrastructures_using_machine_learning.pdf https://strathprints.strath.ac.uk/70936/1/Hindy_etal_CyberICPS2018_Improving_SIEM_for_critical_SCADA_water_infrastructures_using_machine_learning.pdf]

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Hindy et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 526443912 to Hindy et al 2019a

Scipediacontent: Created page with " == Abstract == Network Control Systems (NAC) have been used in many industrial processes. They aim to reduce the human factor burden and efficiently handle the complex proce..."