| Title |
Pattern Detection with Machine Learning and Securing Patterns with Encryption |
| Abstract |
This project aims to address the crucial requirement of protecting patterns identified in datasets during their transmission. The approach involves two main phases: first, utilizing sophisticated pattern recognition algorithms such as AdaBoost Classifier and Random Forest Classifier to extract meaningful insights from the dataset. Second, implementing strong encryption methods, specifically RSA encryption, to safeguard these patterns before they are sent to their destination.
Integrating these phases into a cohesive pipeline enables the secure transmission of patterns to their intended recipients. The project also considers aspects like key management and performance optimization. Comprehensive testing and validation procedures ensure the reliability and efficacy of both the pattern recognition and encryption processes.
By combining advanced pattern recognition with robust encryption techniques, this project offers an optimal solution for securely transmitting valuable insights derived from datasets, ensuring utmost confidentiality and integrity throughout the process
|
| Keywords |
Pattern recognition, AdaBoost and Random Forest classifiers, machine learning algorithms, and encryption and decryption techniques |
| Reserch Area |
Engineering |
| Reserch Paper |
AIJFR2402001 - V2 I2 1-8.pdf |
| Author(s) |
Prakash Sundhe, Gunatit Phani |
| Country |
India |
