Security Frame Towards 6G Networks for Isolating False Data Using Artificial Intelligence Algorithm

This research aims to identify and explore the significance of security aspects in the transition to Sixth Generation (6G) networks. Due to the lack of security features and absence of a data discovery process in the current infrastructure, the proposed approach is being built to discover data under low latency conditions. Furthermore, data analysis is conducted using an artificial intelligence algorithm that incorporates distributed and various decision-making processes to monitor the outcomes. The analysis focuses on the impact of influential factors during data transmission units, employing normalizations to prevent unauthorized users from accessing such transmissions. In order to enhance the security of data in 6G networks, data pairing circumstances are assessed, resulting in increased delivery units at the receiver side and prevention of data drops. In order to conduct a thorough study, the parametric design is evaluated under four different scenarios. The performance analysis is then carried out using two case studies. The results show that the suggested method decreases data drops to 2%, whereas the previous methodology has a data drop rate of 10%.