Securing Personal Data on Smartphones: Addressing APT Challenges and Phishing Threats

 This study examines smartphone security vulnerabilities, with a focus on URL phishing attacks. Our research is organized into two major areas. First, we create a new dataset and use a rigorous feature extraction approach. Second, we present a robust mitigation strategy based on deep learning techniques. Our methodology uses three deep learning models: Convolutional Neural Network (CNN), Deep Neural Network (DNN), and Long Short-Term Memory (LSTM)-each assessed for its effectiveness.