Author Affiliations
[1] [2] [3] [4] Dept. of Computer Science and Engineering, Er. Perumal Manimekalai College of Engineering, Hosur, Tamilnadu, India.
[5] Assistant Professor, Department of Computer Science and Engineering, Er. Perumal Manimekalai College of Engineering, Hosur.
Abstract
This project titled "Automated Phishing email and url detection system" focuses on building an intelligent security solution that helps users identify harmful emails and suspicious web links before any damage occurs, the proposed system uses machine learning techniques along with feature extraction methods to analyze the content of emails and the structure of urls. Various characteristics such as keywords, sender details, link patterns, and text structure are examined to decide whether the given input is safe or malicious. The system is designed to be simple, user-friendly, and efficient so that even non-technical users can benefit from it. By automating the detection process, the project aims to reduce human errors and improve overall cyber safety. The final outcome is expected to be a reliable tool that significantly reduces the risk of phishing attacks and malicious website access
Keywords: Phishing detection, Gemini API, LLM, Naive bayes, logistics regression, Tokenization, TF-IDF, Real-time Detection
How to Cite This Article
K.Jeevitha, M.Jayashree, J.Abinaya, M.Kamalika, Dr.N.Shunmuga Karpagam (2026). Automated Phishing Email and Url Detection System Using Machine Learning and Gemini API. International Journal of Innovative Research in Multidisciplinary Education & Technology (IJIRMET), 11(3).