Aim:
To develop a robust and efficient system for detecting Android malware by leveraging informative syscall subsequences, advanced machine learning, and deep learning models trained on the CICMalDroid2020 dataset.
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.
Aim:
This study develops a machine learning model to classify heart disease into different severity levels. It analyzes patient data to improve diagnostic accuracy and support medical decisions.
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.