入侵容忍数据库系统的半马尔可夫生存能力评估模型

A. Wang, Su Yan, Peng Liu
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引用次数: 17

摘要

生存能力的建模和评估变得越来越重要。大多数现有模型假设状态之间的转换分布是指数分布。然而,这种假设在许多实际情况下并不成立。为了解决这个问题,我们提出了一种新的半马尔可夫生存能力评估模型,该模型允许状态之间的转换遵循非指数分布。还提出了新的定量指标来表征弹性系统抵御入侵的能力。模型验证可能是模型开发生命周期中最重要的一步,但在以往的研究中往往被忽视。本文以一个实际的入侵容忍数据库系统ITDB为例,对所提出的状态空间模型进行了验证。经验实验表明,该半马尔可夫模型对系统行为具有较高的预测精度。此外,我们还评估了系统固有缺陷和攻击行为对入侵容忍数据库系统生存能力的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Semi-Markov Survivability Evaluation Model for Intrusion Tolerant Database Systems
Survivability modeling and evaluation have gained increasing importance. Most existing models assume that the distributions for transitions between states are exponential. However, this assumption does not hold in many real cases. To address this problem, we propose a novel semi-Markov survivability evaluation model, which allows the transitions between states to follow nonexponential distributions. Novel quantitative measures are also proposed to characterize the capability of a resilient system in surviving intrusions. Model validation, which is possibly the most important step in the life cycle of model development, is largely overlooked in previous research. In this paper, a real intrusion tolerant database system ITDB is implemented to validate the proposed state-space models. Empirical experiments show that the semi-Markov model predicts the system behaviors with high accuracy. Furthermore, in this paper we evaluate the impact of intrinsic system deficiencies and attack behaviors on the survivability of intrusion tolerant database systems.
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