Applied Nonlinearity in Modeling Secure Internet Service Dynamics for Academic Library and Research Data Systems

Abstract

Academic library and research-data applications rely more and more on secure, responsive, and reliable information infrastructures, and their performance is dependent upon the nonlinear interactions that happen among the users' demand, the intensity of cyber-threat, the service delay, the trust that the user has, and the adaptive response to threat. The five key state variables of this study are the normalized service load L(t), the intensity of cyber-threats A(t), the level of service trust T(t), the normalized delay D(t) and the security-response level R(t). The model is tested via computational simulation, equilibrium testing, and local stability analysis for five operating conditions, from normal service to the most severe of the security disturbance and adaptive recovery. The criteria for assessing performance is based on the average service load, peak threat intensity, average delay, minimum trust level, recovery time and a Secure Service Performance Index.In the results, severe attack conditions are found to delay and decrease the level of trust, while adaptive response is found to suppress the growth of threat, to gain recovery speed and to enhance secure-service performance, which leads to a resilient academic information-service management.