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Genetic Approximations for the Failure-Free Security Games

机译:无故障安全游戏的遗传近似

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This paper deals with computational aspects of attack trees, more precisely, evaluating the expected adversarial utility in the failure-free game, where the adversary is allowed to re-run failed atomic attacks an unlimited number of times. It has been shown by Buldas and Lenin that exact evaluation of this utility is an NP-complete problem, so a computationally feasible approximation is needed. In this paper we consider a genetic approach for this challenge. Since genetic algorithms depend on a number of non-trivial parameters, we face a multi-objective optimization problem and we consider several heuristic criteria to solve it.
机译:本文涉及攻击树的计算方面,更准确地说,是在无故障游戏中评估预期的对抗性效用,在此游戏中,允许对手无限次重新运行失败的原子攻击。 Buldas和Lenin已经表明,对该实用程序的精确评估是一个NP完全问题,因此需要在计算上可行的近似值。在本文中,我们考虑了应对这一挑战的遗传方法。由于遗传算法取决于许多非平凡的参数,因此我们面临一个多目标优化问题,并考虑了几种启发式准则来解决该问题。

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