信息缺失条件下的相互依存网络抗毁性分析

提出了信息缺失条件下的相互依存网络抗毁性分析方法.首先,提出了结构信息和攻击信息,在结构信息已知的情况下利用信息广度参数和信息精度参数将攻击信息的获取抽象成无放回不等概率抽样问题,以此建立攻击信息缺失模型;然后,借助生成函数和渗流理论的思想提出了在随机信息缺失和优先信息缺失条件下的相互依存网络的抗毁性分析模型.根据此模型可以得到不同情况下的渗流阈值.通过以无标度网络作为实例进行进一步的实验发现信息广度参数和信息精度参数对相互依存网络的渗流阈值影响巨大,并且信息精度比信息广度影响更大,少量的高精度节点信息等价于大量低精度节点信息;已知少量最重要的节点就可以很大程度上降低相互依存网络的抗毁性;即使是在信息缺失的条件下,相互依存网络的抗毁性依旧远低于单层网络.

Survivability analysis of interdependent network with incomplete information

This paper proposed a method for analyzing the survivability of interdependent networks with incomplete information. Firstly, the definition of the structure information and the attack information were proposed. A novel model of interdependent network with incomplete attack information was proposed by considering the process of acquiring attack information as the unequal probability sampling by using information breadth parameter and information accuracy parameter in the condition of structure information was known. Secondly, with the help of generating function and the percolation theory, the interdependent network survivability analysis models with random incomplete information and preferential incomplete information were derived. Finally, the scale-free network was taken as an example for further simulations. The research result shows that both information breadth and information accuracy parameters have tremendous impacts on the percolation threshold of interdependent network, and information accuracy parameter has more impact than information breadth parameter. A small number of high accuracy nodes information has the same survivability performance as a large number of low accuracy nodes information. Knowing a small number of the most important nodes can reduce the interdependent network survivability to a large extent. The interdependent network has far lower survivability performance than the single network even in the condition of incomplete attack information.