A Cognitive Radio Network (CRN) allows Secondary Users (SUs) to sense licensed spectrum in order to transmit if an idle band is detected. Therefore it is imperative that SUs swiftly utilize the spectrum band as soon as it becomes available. This paper proposes a new Generalized Stochastic Petri Net (GSPN) model with intrusion detection to study the impact of scalability on a single node of the CRN towards an effective optimization of an idle band by SUs in cloud computing platforms. In this context, the instant the band becomes idle and there are SU requests waiting for encryption and transmission, additional resources are dynamically released in order to largely utilize the spectrum space before the reappearance of Primary Users (PUs). These extra resources make the same service provision, such as encryption and intrusion detection, as the initial resources. Typical numerical simulation experiments are carried out with and without scalability, based on the application of Mobius Petri Net package, in order to determine the impact of scalability towards the enhancement of nodal CRN sensing, security and performance trade-offs. These results indicate the sustained performance of SUs at the CRN node due to scalability of resources during heavy traffic periods.