uamughal/Cyber-Physical-Intrusion-Detection-System-for-Unmanned-Aerial-Vehicles
This repository contains the code for paper, ''Cyber-Physical Intrusion Detection System for Unmanned Aerial Vehicles,” in IEEE Transactions on Intelligent Transportation Systems (2023)
This project offers a method to detect cyber-attacks on Unmanned Aerial Vehicles (UAVs) by analyzing both their digital network activity and physical flight characteristics. It takes in real-time cyber and physical flight data from a UAV and outputs an alert if an intrusion is detected. This is designed for UAV operators, security analysts, or researchers focused on drone security and safe autonomous operations.
No commits in the last 6 months.
Use this if you need to identify malicious cyber-physical intrusions on UAVs to ensure safe and reliable drone operations.
Not ideal if you are looking for a general-purpose network intrusion detection system not specifically tailored for UAV cyber-physical dynamics.
Stars
12
Forks
1
Language
Python
License
MIT
Category
Last pushed
Feb 25, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/uamughal/Cyber-Physical-Intrusion-Detection-System-for-Unmanned-Aerial-Vehicles"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
AIS-Package/aisp
Artificial Immune Systems Package (AISP) is an open-source Python library that features...
ubc-provenance/PIDSMaker
A framework for building provenance-based intrusion detection systems with neural networks
Western-OC2-Lab/Intrusion-Detection-System-Using-Machine-Learning
Code for IDS-ML: intrusion detection system development using machine learning algorithms...
zimingttkx/Network-Security-Based-On-ML
基于机器学习的网络安全检测系统 | 集成Kitsune/LUCID算法 | 支持ML/DL/RL模型 | 99.58%攻击检测准确率 | 19913 QPS | Docker/K8s部署
Western-OC2-Lab/Intrusion-Detection-System-Using-CNN-and-Transfer-Learning
Code for intrusion detection system (IDS) development using CNN models and transfer learning