  Server Availability (SA) is an important measure of overall systems security.
Important security systems rely on the availability of their hosting servers to
deliver critical security services. Many of these servers offer management
interface through web mainly using an Apache server. This paper investigates
the increase of Server Availability by the use of Artificial Neural Networks
(ANN) to predict software aging phenomenon. Several resource usage data is
collected and analyzed on a typical long-running software system (a web
server). A Multi-Layer Perceptron feed forward Artificial Neural Network was
trained on an Apache web server data-set to predict future server resource
exhaustion through uni-variate time series forecasting. The results were
benchmarked against those obtained from non-parametric statistical techniques,
parametric time series models and empirical modeling techniques reported in the
literature.
