HoneyShield: A Web-Based Honeypot System for Intrusion Detection and Threat Analysis

HoneyShield: A Web-Based Password Attack Detection System for Intrusion Detection and Threat Analysis is a cybersecurity-focused web application designed to detect, monitor, and analyze password-based attacks in real time. With the rapid growth of digital platforms and increasing cyber threats such as brute-force attacks, dictionary attacks, and credential stuffing, securing authentication systems has become critically important. HoneyShield addresses this issue by integrating intelligent monitoring mechanisms and honeypot-based deception techniques to identify malicious login attempts before they compromise sensitive data. The system works by continuously tracking login activities, analyzing suspicious behavior patterns, and detecting multiple failed authentication attempts. When abnormal activities are identified, HoneyShield logs attacker information such as IP address, timestamp, browser details, and attempt frequency for further investigation and threat analysis. A decoy (honeypot) login environment is also implemented to trap attackers and collect behavioral data without exposing real user credentials. Built using modern web technologies and machine learning-based analysis modules, the system provides a real-time dashboard for administrators to monitor attack statistics, visualize intrusion trends, and generate security reports. HoneyShield not only enhances password security but also supports proactive threat intelligence by transforming attack attempts into valuable analytical data. This project demonstrates a practical, scalable, and efficient solution for strengthening web application security through intelligent intrusion detection and attacker monitoring mechanisms. 2.