Abstract
Various threats and security issues exist in the cyber environment. For information assurance, we need to fully understand the concept of Cyber Intelligence (CI) which includes the identification, tracking, analysis and countering of security threats in cyberspace. In order to achieve this, we focus on educating and training CI for organizations and individuals via effective smart systems design and implementation using artificial intelligence (AI) techniques to build an interactive and adaptive learning environment. Based on investigation of basic theories and CI concepts, a simulation model is proposed. Interaction and adaptation are then integrated or designed upon simulation. Such a learning environment aims to impart a thorough and comprehensive understanding of cyber intelligence and provide enhanced learning experience.
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References
Morningstar, C., Farmer, F.R.: The lessons of Lucasfilm’s habitat. In: Cyberspace: First Steps1991, pp. 273–302. MIT Press (1991)
Cone, B.D., et al.: A video game for cyber security training and awareness. Computers & Security 26(1), 63–72 (2007)
Conati, C.: Intelligent tutoring systems: new challenges and directions. In: Proceedings of the 21st International Jont Conference on Artifical Intelligence 2009, pp. 2–7. Morgan Kaufmann Publishers Inc., Pasadena (2009)
Hart, D.G.: Using AMI to realize the Smart Grid. In: 2008 IEEE in Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century (2008)
Momoh, J.: Smart Grid: Fundamentals of Design and Analysis. John Wiley & Sons (2012)
Brown, R.E.: Impact of Smart Grid on distribution system design. In: 2008 IEEE in Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century (2008)
Abbass, H.: computational Red teaming and cyber challenges (2009), http://mams.rmit.edu.au/fpowkftaovbo.pdf
Bennett, C., Highfill, D.: Networking AMI Smart Meters. In: Energy 2030 Conference, ENERGY 2008. IEEE (2008)
McDaniel, P., McLaughlin, S.: Security and Privacy Challenges in the Smart Grid. IEEE Security & Privacy 7(3), 75–77 (2009)
Deb, K., et al.: A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Transactions on Evolutionary Computation 6(2), 182–197 (2002)
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© 2013 Springer-Verlag Berlin Heidelberg
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Zhang, B., Shafi, K., Abbass, H.A. (2013). Robo-Teacher: A Computational Simulation Based Educational System to Improve Cyber Security. In: Kim, JH., Matson, E., Myung, H., Xu, P. (eds) Robot Intelligence Technology and Applications 2012. Advances in Intelligent Systems and Computing, vol 208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37374-9_18
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DOI: https://doi.org/10.1007/978-3-642-37374-9_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-37373-2
Online ISBN: 978-3-642-37374-9
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