PHISHCATCHER CLIENT-SIDE DEFENSE AGAINST WEB SPOOFING

Abstract

Web spoofing and phishing attacks continue to pose significant threats to users by deceiving them into revealing sensitive information such as login credentials, financial details, and personal data. Traditional server-side detection mechanisms often fail to provide real-time protection at the user level, especially against sophisticated attacks that dynamically mimic legitimate websites. To address these challenges, this project proposes PhishCatcher: A Client-Side Defense System Against Web Spoofing, designed to detect and prevent phishing attacks directly within the user’s browsing environment. The system leverages advanced machine learning and heuristic analysis techniques to identify malicious web pages based on features such as URL structure, domain similarity, page content, visual layout, and SSL certificate validation. The proposed approach integrates a lightweight browser-based module that continuously monitors user interactions and webpage characteristics in real time. It employs feature extraction mechanisms to analyze suspicious patterns such as homoglyph attacks, abnormal redirects, and hidden elements. A trained classification model, such as a Random Forest or Deep Learning model, evaluates these features to determine the legitimacy of a website. Additionally, the system incorporates visual similarity detection by comparing webpage screenshots with known legitimate sites, enhancing its ability to detect sophisticated spoofing attacks. Experimental results demonstrate that PhishCatcher achieves high detection accuracy while maintaining low latency, ensuring a seamless user experience. Unlike traditional approaches, the client-side architecture enables immediate threat detection without relying on external servers, thereby improving privacy and responsiveness. The system is scalable, adaptable to evolving phishing techniques, and can be integrated into modern web browsers as an extension. Overall, this research contributes to enhancing cybersecurity by providing an intelligent, real-time, and user-centric defense mechanism against web spoofing attacks.