Keylogger Detection Project using Python Tkinter
Keyloggers are a prevalent threat that record users’ keystrokes to steal credentials and sensitive data. This paper presents a Python-based keylogger detection tool that scans running processes and checks them against indicators of compromise (IOCs). The detector integrates process inspection, signature matching, and automated remediation functions. A graphical user interface allows easy operation and threat response. The tool was tested against known keyloggers and demonstrated effective discovery with minimal false positives. This demonstrates Python’s capabilities for building specialized security automation scripts to fill gaps in traditional anti-malware. The detector provides a straightforward yet extensible approach for defending against keylogging threats.
The Domain of Information technology is rapidly evolving in today’s world. The major problem is privacy and security for cyber professionals. Number of new malware is rapidly increasing from recent studies. A keylogger is a highly sophisticated malware that records every keystroke made on machine, it allows the attacker to steal sensitive information without authorization of actual owner. Identification of keylogger is much important to avoid data loss and information leaking. Keylogger can be detected by antivirus via heuristic and behavior analysis, but if keylogger is not a known threat, then anti-malware or antivirus cannot detect it as a virus.
Machine Learning is approach to detect keylogger that perform various hazardous activities performed by keyloggers in computers. The Keylogger program generates a variety of patterns or keystrokes.
Detect keyloggers by using Machine Learning
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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