Abstract
Moving Target Defense (MTD) has the potential to increase the cost and complexity for threat actors by creating asymmetric uncertainty in the cyber security landscape. The tactical advantages that MTD can provide to the defender have led to the development of a vast array of diverse techniques, which are designed to operate under different constraints and against different classes of threats. Due to the diverse nature of these various techniques and the lack of shared metrics to assess their benefits and cost, comparing multiple techniques is not a trivial task. We addressed this gap by designing a framework to enable a uniform approach to the analysis and quantification of MTD techniques. This framework looks at each MTD technique in terms of the attacker’s knowledge it is capable of compromising, thus enabling direct comparison of any two techniques or set of techniques.
The work presented in this chapter was supported by the Army Research Office under grant W911NF-13-1-0421.
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Albanese, M., Connell, W., Venkatesan, S., Cybenko, G. (2019). Moving Target Defense Quantification. In: Jajodia, S., Cybenko, G., Liu, P., Wang, C., Wellman, M. (eds) Adversarial and Uncertain Reasoning for Adaptive Cyber Defense. Lecture Notes in Computer Science(), vol 11830. Springer, Cham. https://doi.org/10.1007/978-3-030-30719-6_5
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