Reasoning about Moving Target Defense in Attack Modeling Formalisms

TL;DR

This paper introduces a new DAG-based formalism for Moving Target Defense (MTD), translating it into a Price Timed Markov Decision Process to optimize activation frequencies against attack strategies, with experimental validation.

Contribution

It presents the first DAG-based formalism for MTDs, enabling automatic analysis and optimization of activation frequencies in attack modeling.

Findings

First analysis of MTD activation frequencies in DAG-based attack models

Translation into Price Timed Markov Decision Process for optimization

Experimental validation using Uppaal Stratego

Abstract

Since 2009, Moving Target Defense (MTD) has become a new paradigm of defensive mechanism that frequently changes the state of the target system to confuse the attacker. This frequent change is costly and leads to a trade-off between misleading the attacker and disrupting the quality of service. Optimizing the MTD activation frequency is necessary to develop this defense mechanism when facing realistic, multi-step attack scenarios. Attack modeling formalisms based on DAG are prominently used to specify these scenarios. Our contribution is a new DAG-based formalism for MTDs and its translation into a Price Timed Markov Decision Process to find the best activation frequencies against the attacker's time/cost-optimal strategies. For the first time, MTD activation frequencies are analyzed in a state-of-the-art DAG-based representation. Moreover, this is the first paper that considers the specificity of MTDs in the automatic analysis of attack modeling formalisms. Finally, we present some experimental results using Uppaal Stratego to demonstrate its applicability and relevance.