International Journal of Scientific Research and Engineering Development

One of the most significant cybersecurity concerns is phishing attacks. Phishing attacks are mostly carried out through malicious links, fake websites, and QR code scams. The conventional way of detecting these attacks is through static blacklisting. However, this is not an efficient way of detecting newly generated phishing sites. In this project, an AI-Powered Phishing Detection Web Application with an Accessibility Assistant is proposed. In this web application, the URL will be scanned in real time and classified as safe, suspicious, or phishing based on its characteristics such as its domain structure, presence of HTTPS, length of the URL, and presence of suspicious keywords. The web application also offers easy visualization of risks with the help of colors. In addition, an AI Robot Assistant with multiple languages and text-to-speech functionality is also offered to assist users in scanning the websites. In order to improve user awareness and usability, it also offers scan history and frequently visited sites. In this project, an efficient solution is proposed in the form of a lightweight web-based platform with an intuitive interface suitable for nontechnical users, which can help in improving accuracy in detecting phishing sites.

Shifa Bilal Tamboli, Simeen Phiroj Mulani, Arman Tajuddin Shiakh,"Smart Phishing Detection System With Adaptive Threat Intelligence" International Journal of Scientific Research and Engineering Development, V9(2): Page(2396-2402) Mar-Apr 2026. ISSN: 2581-7175. www.ijsred.com. Published by Scientific and Academic Research Publishing.