Clairvoyant targeted attack on complex networks Online publication date: Mon, 04-Dec-2017
by Giovanna Ferraro; Antonio Iovanella
International Journal of Computational Economics and Econometrics (IJCEE), Vol. 8, No. 1, 2018
Abstract: Complex networks' resilience against attacks represents a crucial issue in terms of network structure integrity. We investigate the effect of removing nodes on the network diameter in the case of a simultaneous targeted attack and sequential targeted attack. The analysis has been implemented on several network instances, taking into account different centrality measures and clustering coefficients values. Empirical networks have also been observed to compare the effects of the two removal schemes. According to classical literature, we assume that the network attacker has a wide-ranging knowledge of the system. It can be defined as clairvoyant since it knows, a priori, of all the characteristics of the problem's instances. This awareness is not always applicable when real networks are characterised by a dynamic environment. Hence, we distinguish between clairvoyant and non-clairvoyant attacks.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Economics and Econometrics (IJCEE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com