Authors: Dr Y Subba Reddy, A Guru Jyotshna, K Deepthi, B Paramesh, D.Siva Ganga Keerthi
Abstract: Neuroplasticity, as the name suggests, refers to the brain's remarkable ability to reorganize itself by forming new connections throughout life. Neuroplasticity has been observed to be more active in early childhood, as the processes of synaptic pruning and myelination are more active during this period. Research has shown that environmental stimulation has a direct effect on the thickness of the cortex, as well as the dendritic branching patterns of the neurons. Functional magnetic resonance imaging has shown that the brains of adults have a lot of plasticity, which enables the brains to recover from injury as well as to learn new skills. The neuroplasticity framework has a lot of implications, especially in the field of educational psychology as well as rehabilitation medicine. Experimental results using crawled Tor URL datasets demonstrate that the proposed method achieves 97.50% accuracy, outperforming conventional CNN-based deep fingerprinting techniques. Further optimization is achieved by incorporating a BiGRU layer after LSTM, enabling bidirectional feature extraction and improving prediction performance to 97.86%. Performance metrics including precision, recall, F1-score, and confusion matrices confirm the enhanced effectiveness of this methodology for distinguishing normal and attack-type Tor services, providing a robust framework for secure network monitoring.
DOI: https://doi.org/10.5281/zenodo.19060572
