\mathsf QFlip - An Adaptive Reinforcement Learning Strategy for the \mathsf FlipIt Security Game

Lisa Oakley
Lisa Oakley

GameSec, pp. 364-384, 2019.

Cited by: 0|Bibtex|Views32|DOI:https://doi.org/10.1007/978-3-030-32430-8_22
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Other Links: dblp.uni-trier.de|academic.microsoft.com

Abstract:

A rise in Advanced Persistent Threats (APTs) has introduced a need for robustness against long-running, stealthy attacks which circumvent existing cryptographic security guarantees. \\(\\mathsf {FlipIt}\\) is a security game that models attacker-defender interactions in advanced scenarios such as APTs. Previous work analyzed extensively n...More

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