Keylogger Detection System with Real-Time Notification

Abstract

In the modern digital age, the use of computers and internet-based systems has become an essential part of everyday life. From online banking and e-commerce to communication and education, people rely heavily on digital platforms to perform various activities. However, this rapid growth in digital dependency has also led to an increase in cyber threats and security vulnerabilities. One of the most dangerous forms of malware used by attackers is a keylogger, which is designed to secretly record the keystrokes of a user without their knowledge. These keystrokes often include sensitive information such as usernames, passwords, credit card details, and private communications, making keyloggers a serious threat to personal and organizational security.

The proposed Keylogger Detection System with Real-Time Notification aims to provide a robust and efficient solution to this problem. Instead of relying solely on traditional signature-based detection methods, the system uses behavioral analysis techniques to monitor system activities continuously. It observes how applications interact with keyboard inputs and identifies suspicious patterns that may indicate keylogging behavior. Once such activity is detected, the system immediately generates a real-time notification to alert the user, allowing them to take quick preventive measures. This approach not only enhances detection accuracy but also significantly reduces the response time, thereby minimizing potential damage caused by keylogging attacks.