Smart Phishing Detection Application

Abstract

Phishing attacks remain a grave cybersecurity concern, especially on mobile operating systems where people are more vulnerable to imitated URLs. This paper introduces the Smart Phishing Detection Application, an intelligent Android- based application that detects phishing URLs in real-time using a hybrid mechanism. The mobile app cooperates well with a backend powered by an XGBoost machine learning powerhouse and threat intelligence APIs like VirusTotal and Google Safe Browsing. Scanning or entering suspicious URLs, which are checked and assigned a phishing threat score, can be done by users. Our technology combines machine learning-based predictions with third-party threat feeds to provide better detection while minimizing false positives. This application is designed to be easy to use, scalable, and efficient in providing mobile users timely phishing alerts, encouraging individual cybersecurity while in transit.

KEYWORDS: Phishing Detection, Machine Learning, XGBoost, Android Security, Threat Intelligence, Real-time Analysis