Analysing distributed Internet worm attacks using continuous state-space approximation of process algebra models
Analysing distributed Internet worm attacks using continuous state-space approximation of process algebra models
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DOI：
10.1016/j.jcss.2007.07.005
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发表时间：
2008-09
期刊：
影响因子：
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通讯作者：
Jeremy T. Bradley;S. Gilmore;J. Hillston
中科院分区：
文献类型：
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作者：
Jeremy T. Bradley;S. Gilmore;J. Hillston
互联网蠕虫的经典描述使用SIR模型和模拟，以捕捉系统的大规模动态。在这里，我们能够生成一个基于微分方程的感染模型的基础上，感染代理模型的底层过程描述。因此，我们不是直接创建微分方程模型，而是从PEPA过程代数中表示的高级过程模型自动导出此表示。这扩展了现有的人口感染动力学模型的互联网蠕虫明确使用频率为基础的传播感染。三种类型的蠕虫攻击进行了分析，这是区分的性质恢复感染和脆弱性，随后的攻击。为了进行这种分析，我们利用连续状态空间近似，最近在大规模并行随机过程代数模型的分析突破。以前的显式状态表示技术只能分析109阶状态的系统，而连续状态空间近似可以分析1010000阶状态及以上的模型。
Internet worms are classically described using SIR models and simulations, to capture the massive dynamics of the system. Here we are able to generate a differential equation-based model of infection based solely on the underlying process description of the infection agent model. Thus, rather than craft a differential equation model directly, we derive this representation automatically from a high-level process model expressed in the PEPA process algebra. This extends existing population infection dynamics models of Internet worms by explicitly using frequency-based spread of infection. Three types of worm attack are analysed which are differentiated by the nature of recovery from infection and vulnerability to subsequent attacks. To perform this analysis we make use of continuous state-space approximation, a recent breakthrough in the analysis of massively parallel stochastic process algebra models. Previous explicit state-representation techniques can only analyse systems of order 109states, whereas continuous state-space approximation can allow analysis of models of 1010000states and beyond.