IoT Network Attack Detection
A multi-class machine learning project detecting IoT network attacks using behavioral time-window traffic features from a 27M packet dataset.
- - Processed and sampled from a 27M packet IoT network dataset.
- - Built multi-class classification models to detect SYN DoS, ARP MitM, Mirai, and other attacks.