Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA.
Department of Mathematics and Statistics, University of Nevada, Reno, NV, USA.
Sci Rep. 2017 Aug 17;7(1):8567. doi: 10.1038/s41598-017-08714-3.
Network robustness against attacks has been widely studied in fields as diverse as the Internet, power grids and human societies. But current definition of robustness is only accounting for half of the story: the connectivity of the nodes unaffected by the attack. Here we propose a new framework to assess network robustness, wherein the connectivity of the affected nodes is also taken into consideration, acknowledging that it plays a crucial role in properly evaluating the overall network robustness in terms of its future recovery from the attack. Specifically, we propose a dual perspective approach wherein at any instant in the network evolution under attack, two distinct networks are defined: (i) the Active Network (AN) composed of the unaffected nodes and (ii) the Idle Network (IN) composed of the affected nodes. The proposed robustness metric considers both the efficiency of destroying the AN and that of building-up the IN. We show, via analysis of well-known prototype networks and real world data, that trade-offs between the efficiency of Active and Idle Network dynamics give rise to surprising robustness crossovers and re-rankings, which can have significant implications for decision making.
网络对攻击的鲁棒性已在互联网、电网和人类社会等多个领域得到广泛研究。但目前的鲁棒性定义仅考虑了故事的一半:不受攻击影响的节点的连通性。在这里,我们提出了一个新的框架来评估网络鲁棒性,其中还考虑了受影响节点的连通性,因为它在从攻击中恢复的角度正确评估整体网络鲁棒性方面起着至关重要的作用。具体来说,我们提出了一种双重视角方法,其中在攻击下的网络演化的任何时刻,都定义了两个截然不同的网络:(i) 由未受影响的节点组成的主动网络 (AN) 和 (ii) 由受影响的节点组成的空闲网络 (IN)。所提出的鲁棒性度量考虑了破坏 AN 和建立 IN 的效率。我们通过对知名原型网络和真实世界数据的分析表明,主动和空闲网络动态之间的效率权衡会导致令人惊讶的鲁棒性交叉和重新排序,这对决策可能产生重大影响。