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Title: | Evaluation of anomaly detection based on classification in relation to SCADA |
Author: | Vávra, Jan; Hromada, Martin |
Document type: | Conference paper (English) |
Source document: | ICMT 2017 - 6th International Conference on Military Technologies. 2017, p. 330-334 |
ISBN: | 978-1-5386-1988-9 |
DOI: | https://doi.org/10.1109/MILTECHS.2017.7988779 |
Abstract: | The accelerating development of information and communication technologies have an eminent influence on contemporary society. As a result, we have an opportunity to increase our effectiveness. However, there is a drawback. Contemporary systems becoming much more interconnected and opened. However, it negatively affects cyber security of Supervisory Control and Data Acquisition (SCADA) systems. Therefore, the reliable security system must be applied in order to increase system resilience. The article deals with widely used systems for intrusion detection (IDS). These systems are an indispensable basis for cyber security of every organization. The aim of the article is to evaluate an anomaly detection predictive models based on classification. © 2017 IEEE. |
Full text: | http://ieeexplore.ieee.org/abstract/document/7988779/ |
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