Abstract
The use of tools for monitoring the security state of assets in a network is an essential part of network management. Traditional risk assessment methodologies provide a framework for manually determining the risks of assets, and intrusion detection systems can provide alerts regarding security incidents, but these approaches do not provide a real-time high level overview of the risk level of assets. In this paper we further extend a previously proposed real-time risk assessment method to facilitate more flexible modeling with support for a wide range of sensors. Specifically, the paper develops a method for handling continuous-time sensor data and for determining a weighted aggregate of multisensor input.
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References
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Haslum, K., Årnes, A. (2007). Multisensor Real-Time Risk Assessment Using Continuous-Time Hidden Markov Models. In: Wang, Y., Cheung, Ym., Liu, H. (eds) Computational Intelligence and Security. CIS 2006. Lecture Notes in Computer Science(), vol 4456. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74377-4_72
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DOI: https://doi.org/10.1007/978-3-540-74377-4_72
Publisher Name: Springer, Berlin, Heidelberg
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