ADVANCED KEYLOGGER FOR SYSTEM MONITORING A Modular, Ethical Framework for Cybersecurity Education and Behavioral Analysis

ABSTRACT

This study introduces a controlled and ethically governed investigation into an Advanced Keylogger and Secure Monitoring Framework developed for use in isolated cybersecurity laboratory environments. The project centers on a modular Python- based architecture that employs libraries such as pynput, pyautogui, and AES encryption to record keystroke data, secure it through cryptographic methods, and present activity metrics using a tkinter-driven graphical interface. The system is designed to act as a research-oriented monitoring tool that addresses the transparency and security shortcomings of conventional keyloggers.

Emphasis is placed on ethical compliance, data protection, and the educational value of the platform. The framework enables cybersecurity students and analysts to safely examine key logging behavior, evaluate detection strategies, and strengthen defensive programming capabilities within a sandboxed environment. Comprehensive documentation of the system’s structure, implementation process, and controlled experimental evaluation is provided to demonstrate its utility as a bridge between conceptual cybersecurity instruction and practical threat emulation.

Keywords

Advanced Keylogger, Modular architecture, AES encryption, CBC mode, pynput, pyautogui, sandboxed environment, secure monitoring, cybersecurity education.