Early Detection of Childhood Malnutrition using Survey Data and Machine Learning Approaches

5,500.00

Aim: To develop a predictive model for early detection of childhood malnutrition using survey-based health and nutrition data, and to compare the performance of ensemble and classical machine learning algorithms.

Evolving Malware and DDoS Attacks: Decadal Longitudinal Study

5,500.00
Aim: To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.

Neural-XGBoost A Hybrid Approach for Disaster Prediction and Management Using Machine Learning

5,500.00

Aim

Ā  Ā  Ā  Ā  Ā  To develop a four-class disaster prediction system that uses SMOTE for class balancing, evaluates four advanced machine learning models, selects the best-performing classifier, and deploys it through an interactive web interface

 

Rule-Based With Machine Learning IDS for DDoS Attack Detection in Cyber-Physical Production Systems (CPPS)

5,500.00

To enhance DDoS attack detection by implementing a machine learning system with hyperparameter optimization and advanced prediction techniques, utilizing the CICIDS dataset to achieve high classification accuracy and improve network security.