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Quantifying mixed uncertainties in cyber attacker payoffs

Authors :
Mahantesh Halappanavar
Matthew Oster
Samrat Chatterjee
Sudip Saha
Ramakrishna Tipireddy
Source :
2015 IEEE International Symposium on Technologies for Homeland Security (HST).
Publication Year :
2015
Publisher :
IEEE, 2015.

Abstract

Representation and propagation of uncertainty in cyber attacker payoffs is a key aspect of security games. Past research has primarily focused on representing the defender's beliefs about attacker payoffs as point utility estimates. More recently, within the physical security domain, attacker payoff uncertainties have been represented as Uniform and Gaussian probability distributions, and intervals. Within cyber-settings, continuous probability distributions may still be appropriate for addressing statistical (aleatory) uncertainties where the defender may assume that the attacker's payoffs differ over time. However, systematic (epistemic) uncertainties may exist, where the defender may not have sufficient knowledge or there is insufficient information about the attacker's payoff generation mechanism. Such epistemic uncertainties are more suitably represented as probability boxes with intervals. In this study, we explore the mathematical treatment of such mixed payoff uncertainties.

Details

Database :
OpenAIRE
Journal :
2015 IEEE International Symposium on Technologies for Homeland Security (HST)
Accession number :
edsair.doi...........11ca5c1839a7244ba4ae1df5e7cd2a77