I love building clean, human-centered digital experiences—whether it's designing intuitive interfaces or diving deep into code. Currently exploring full-stack
Hybrid DDoS detection system combining Autoencoder and Random Forest. The Autoencoder detects anomalies in network traffic, while Random Forest classifies traffic as benign or malicious. Trained on CIC-DDoS2019 dataset, the model achieves high accuracy and improved detection of unknown attacks.
🔐 URL Phishing Detection using Machine Learning This project implements a machine learning–based system to detect phishing URLs by analyzing their structural and lexical features. The model classifies URLs as phishing or legitimate using feature extraction techniques and classical ML algorithms such as Logistic Regression and Random Forest.
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