Keylogger Detector - Technical & Engineering Guide
1. Introduction
1.1 Purpose
This guide outlines the steps to design and implement a Keylogger Detector. The system aims to identify and neutralize malicious keyloggers to protect user privacy and security.
1.2 Scope
The Keylogger Detector is suitable for individual users, organizations, and IT professionals. It provides a proactive approach to identifying keyloggers using signature-based detection, heuristic analysis, and behavioral monitoring.
1.3 Definitions & Acronyms
|
Acronym |
Definition |
|
Keylogger |
A program that records every keystroke made on a computer. |
|
Signature |
A unique identifier of known malware. |
|
Heuristic Analysis |
A technique to detect malware by examining its behavior. |
|
Behavioral Monitoring |
Analyzing software actions in real-time to detect anomalies. |
2. System Architecture
The architecture of the Keylogger Detector includes:
- **Signature Database**: Maintains known keylogger patterns.
- **Heuristic Engine**: Analyzes processes and activities to identify
suspicious behavior.
- **Real-Time Monitor**: Tracks system activities for real-time detection.
- **Reporting Module**: Provides alerts and logs for detected keyloggers.
3. Key Features
3.1 Signature-Based Detection
Compares running processes and files against a database of known keylogger signatures.
3.2 Behavioral Analysis
Monitors suspicious activities such as unauthorized logging of keystrokes or frequent file access.
3.3 Real-Time Alerts
Provides immediate notifications for detected keylogger activities.
4. Implementation Steps
1. **Environment Setup**: Install necessary tools and
libraries (Python, psutil, etc.).
2. **Signature Database Creation**: Compile a list of known keylogger patterns.
3. **Heuristic Rules Development**: Define rules for detecting suspicious
behavior.
4. **Real-Time Monitoring**: Implement a module to monitor running processes
and activities.
5. **User Interface**: Design a simple interface for alerts and reports.
6. **Testing**: Validate the system with both benign and malicious software.
7. **Deployment**: Package the detector for distribution.
5. Security Considerations
1. Regularly update the signature database.
2. Use sandboxing to safely analyze unknown processes.
3. Ensure that the detector itself is protected against tampering.
6. Tools and Technologies
- **Programming Language**: Python
- **Libraries**: psutil, pywin32
- **Signature Database**: SQLite or JSON file
- **User Interface**: Tkinter, PyQt
7. Testing and Validation
1. Test with known keyloggers to evaluate detection
accuracy.
2. Simulate benign activities to verify false-positive rates.
3. Conduct performance tests to ensure minimal system impact.