Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{180020,
        author = {Harish Kumar and Bhavya R A and G V Kiran and Chethan P M and Gagan B V},
        title = {Machine Learning Enabled Character Based Encryption},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {12},
        number = {1},
        pages = {485-489},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=180020},
        abstract = {As the demand for secure communication 
grows, encryption methods have advanced to address 
complex cyber threats. This study introduces a 
Machine 
Learning 
Enabled 
Character-Based 
Encryption System (MLE-CBES) that utilizes artificial 
intelligence to bolster data protection. The system 
integrates conventional cryptographic techniques with 
machine learning models to develop adaptive 
encryption strategies based on character patterns. In 
this method, the machine learning model is trained on 
diverse text datasets to dynamically learn and predict 
optimal encryption keys, making it more difficult for 
unauthorized parties to decrypt the data. The 
encryption 
process 
involves 
character-level 
transformations, encoding text into a more intricate 
cipher through contextual and probabilistic analysis. 
Unlike traditional encryption methods that use static 
keys, the machine learning component ensures the 
continuous 
evolution 
of 
encryption 
patterns, 
enhancing security against brute-force and pattern
based attacks. Experiments show that the MLE-CBES 
significantly enhances encryption strength while 
maintaining 
computational 
efficiency. 
The 
incorporation of machine learning offers adaptability 
and randomness, making it a promising solution for 
secure 
data 
transmission 
communication systems.},
        keywords = {Encryption, Machine Learning, Character-  Based Encryption, Cybersecurity, Adaptive Security  cyber threats while maintaining low latency and high  performance for real-world communication. detection},
        month = {May},
        }