DETECTION AND PREVENTION OF WEBSITE CREDENTIAL HARVESTING ATTACKS THROUGH SECURITY MONITORING TECHNIQUES

Abstract

Credential harvesting attacks have emerged as one of the most prevalent and dangerous cyber threats targeting individuals and organizations in the digital era. These attacks involve the unauthorized collection of sensitive user information such as usernames, passwords, and other authentication details through malicious websites, phishing pages, or compromised login forms. Once obtained, attackers exploit these credentials to gain unauthorized access to systems, financial accounts, and confidential data, leading to severe security and privacy breaches.
This project focuses on the detection and prevention of website credential harvesting attacks through advanced security monitoring techniques. The proposed system continuously monitors web traffic and analyzes user login activities to identify suspicious patterns and potential phishing attempts. It utilizes a combination of rule-based detection methods, traffic analysis, and log monitoring to detect abnormal behaviors associated with credential theft.
Additionally, the system incorporates preventive mechanisms such as domain verification, anomaly detection, real-time alerts, and browser-level security enhancements to block malicious activities before user credentials are compromised. By integrating network monitoring tools and intelligent detection strategies, the system ensures proactive identification and mitigation of threats.