https://github.com/aishwaryagm1999/aircraft-network-security-using-yara-rules-and-machine-learning-for-threat-detection-and-prevention

This project addresses cybersecurity in aviation by developing a machine learning-enhanced intrusion detection and prevention system (IDPS) for aircraft networks. Combining YARA-based signature detection with behavior-based (ML) anomaly detection, the system mitigates cyber threats in real-time, protecting aircraft from sophisticated attacks.
https://github.com/aishwaryagm1999/aircraft-network-security-using-yara-rules-and-machine-learning-for-threat-detection-and-prevention

argus automation cybersecurity feature-hashing idps joblib machine-learning matplotlib networking numpy pandas python random-forest-classifier requests seaborn shell smote smotesmote tshark yara

Last synced: 14 days ago
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This project addresses cybersecurity in aviation by developing a machine learning-enhanced intrusion detection and prevention system (IDPS) for aircraft networks. Combining YARA-based signature detection with behavior-based (ML) anomaly detection, the system mitigates cyber threats in real-time, protecting aircraft from sophisticated attacks.

• Host: GitHub
• URL: https://github.com/aishwaryagm1999/aircraft-network-security-using-yara-rules-and-machine-learning-for-threat-detection-and-prevention
• Owner: aishwaryagm1999
• Created: 2024-11-02T18:57:25.000Z (15 days ago)
• Default Branch: main
• Last Pushed: 2024-11-02T19:11:25.000Z (15 days ago)
• Last Synced: 2024-11-02T19:27:46.777Z (15 days ago)
• Topics: argus, automation, cybersecurity, feature-hashing, idps, joblib, machine-learning, matplotlib, networking, numpy, pandas, python, random-forest-classifier, requests, seaborn, shell, smote, smotesmote, tshark, yara
• Language: Python
• Homepage:
• Size: 0 Bytes
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Aircraft-Network-Security-using-YARA-Rules-and-Machine-Learning-for-Threat-Detection-and-Prevention

## Overview

This project introduces an Intrusion Detection and Prevention System (IDPS) specifically designed for the unique cybersecurity requirements of aircraft networks. Leveraging YARA for signature-based detection alongside machine learning for anomaly detection, this system enhances security by identifying and mitigating cyber threats in real time. The IDPS integrates both signature and behavior-based patterns, providing robust protection for aircraft networks from cyber threats like malware, DDoS attacks, and unauthorized access attempts.

## Features

- **Signature-Based Detection**: Utilizes YARA rules for malware signature detection.

- **Machine Learning Anomaly Detection**: Employs random forest classifiers and feature hashing for behavior-based threat identification.

- **Real-Time Alerts**: Sends instant alerts to pilots and ground control upon detecting threats.

- **Incident Response**: Implements automated responses, including blocking IPs and restricting access to compromised zones.