Modern communication systems need strong security measures due to their growing complexity. There is a pressing need for improved access models since current cognitive radio networks are susceptible to attacks. By thoroughly analysing each and every network transaction, the Zero Trust Access Model (ZTAM) offers a safe paradigm. This research is driven by the need to strengthen CRNs and seeks to evaluate and maximise the effect of ZTAM. Utilizing the Red Deer Algorithm has the potential to optimise parameters, enhancing performance and security. Cognitive radio networks (CRNs) that use the Red Deer Algorithm and a Zero Trust Access Model (ZTAM) are the focus of this study's performance evaluation and optimization efforts. While studies concentrate on studying and improving the network's efficiency, the ZTAM guarantees a rigorous security approach. This research uses the Red Deer Algorithm to optimise CRN functionality in the ZTAM framework by adjusting system settings. Throughput and energy efficiency are the metrics used to evaluate the system's performance in the research. The paper presents an optimization problem aimed at optimising energy efficiency and throughput simultaneously. Parameters are adjusted using the Red Deer Algorithm (RDA). In order to get a better understanding of how the system behaves under different system and channel circumstances, we provide simulation findings obtained using the ZTAM-RDA configuration.
Key words: Performance Analysis; Optimization; Cognitive Radio Networks; Zero Trust Access Model (ZTAM); Red Deer Algorithm; Security Enhancement.
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