Authors: Zhanshan Sam Ma
Addresses: Computational Biology and Medical Ecology Laboratory, National Key Laboratory of Genetic Resources and Evolution, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Departments of Computer Science and Biological Sciences and Institute of Bioinformatics and Evolutionary Studies (iBEST), University of Idaho, Moscow, ID, USA
Abstract: The common usage of the term frailty, which literally means the condition (quality) of being frail or a fault, may be too ambiguous to be very useful for characterising network security. Nevertheless, the mathematical concept of frailty, which originated in the study of aging and demography, may offer a powerful approach for analysing the risks in network security and survivability. This is because network security analysis is essentially a risk analysis problem, and identifying risks, especially those that are uncertain, latent, unobserved or unobservable (UUUR) (Ma, 2008), and further analysing the potential dependence between those risks are two critical challenges for risk analysis in any field. Frailty modelling excels in addressing these two challenges. When it is integrated with dynamic hybrid fault models (DHF) and extended evolutionary game theory (EEGT) (Ma and Krings, 2011), frailty modelling should provide powerful approaches for analysing risks in network security and survivability.
Keywords: frailty modelling; survival analysis; network security; survivability; demography; population hazard function; individual hazard function; risk assessment; hybrid fault models; extended evolutionary game theory.
International Journal of Information and Computer Security, 2011 Vol.4 No.3, pp.276 - 294
Available online: 19 May 2011Full-text access for editors Access for subscribers Purchase this article Comment on this article