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Conference proceeding
Scenario-based Learning Approach to Industrial Control Systems Security Training
Proceedings of the International Conference on Security and Management (SAM), pp.111-116
The 2018 WorldComp International Conference Proceedings
International Conference on Security and Management (SAM), 16th (Luxor hotel, Las Vegas, Nevada, USA, 07/29/2018–08/02/2018)
01/01/2018
Abstract
Recognizing the need for a trained workforce that can protect the Industrial Control Systems, we embarked on a project to develop scenario-based training materials and a hybrid testbed for industrial control systems security with the following objectives: to develop, implement, and test curriculum modules with virtual scenario-based laboratory exercises focused on industrial control systems (ICS) security, to design and implement a prototypical testbed for a distributed virtual ICS/SCADA system that can be used for virtual scenarios-based exercises, to disseminate and share these curriculum modules with the ICS security training centers and educational institutions, and to evaluate teaching and learning effectiveness of these Industrial Control Systems (ICS) security curriculum.
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Details
- Title
- Scenario-based Learning Approach to Industrial Control Systems Security Training
- Publication Details
- Proceedings of the International Conference on Security and Management (SAM), pp.111-116
- Resource Type
- Conference proceeding
- Conference
- International Conference on Security and Management (SAM), 16th (Luxor hotel, Las Vegas, Nevada, USA, 07/29/2018–08/02/2018)
- Publisher
- The Steering Committee of The World Congress in Computer Science, Computer Engineering and Applied Computing (WorldComp); Athens
- Series
- The 2018 WorldComp International Conference Proceedings
- Grant note
- This work is supported in part by a Center for Academic Excellence (CAE) Cyber Security Research Program grant (Award # H98230-17-1-0326) from the National Security Agency (NSA) and a National Science Foundation (NSF) grant (Award # 1515636). Opinions expressed are those of the author and not necessarily of the granting agencies.
- Copyright
- CSREA Press ©
- Identifiers
- 99380558193306600
- Academic Unit
- Center for Cybersecurity and AI
- Language
- English