Defender Policy Evaluation and Resource Allocation Using MITRE ATT&CK Evaluations Data

arXiv (Cornell University)(2021)

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摘要
Protecting against multi-step attacks of uncertain duration and timing forces defenders into an indefinite, always ongoing, resource-intensive response. To effectively allocate resources, a defender must be able to analyze multi-step attacks under assumption of constantly allocating resources against an uncertain stream of potentially undetected attacks. To achieve this goal, we present a novel methodology that applies a game-theoretic approach to the attack, attacker, and defender data derived from MITRE's ATT&CK Framework. Time to complete attack steps is drawn from a probability distribution determined by attacker and defender strategies and capabilities. This constraints attack success parameters and enables comparing different defender resource allocation strategies. By approximating attacker-defender games as Markov processes, we represent the attacker-defender interaction, estimate the attack success parameters, determine the effects of attacker and defender strategies, and maximize opportunities for defender strategy improvements against an uncertain stream of attacks. This novel representation and analysis of multi-step attacks enables defender policy optimization and resource allocation, which we illustrate using the data from MITRE's APT3 ATT&CK Evaluations.
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关键词
Markov processes, Measurement, Resource management, Games, Security, Steady-state, Estimation, cyber security, MITRE ATT&CK, game theory, Markov chains, attacker, defender, attack graphs, attack, physics of attacks, stochastic process, probability theory, optimization, optimal policy, PLADD, GPLADD
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