🔐 Key Fob Security Analysis

📌 Overview

This project focuses on analyzing wireless key fob security using captured RF signals.
It includes replay attack analysis, rolling code detection, bitstream decoding, and signal/data analysis using the Pearson correlation coefficient.

The workflow is designed for controlled security research and academic purposes only.

⚠️ Disclaimer: Use only on devices you own or have explicit permission to test. Unauthorized use may be illegal in your country.

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📂 Project Structure

📦 keyfob-security-analysis ┣ 📜 README.md # Project documentation ┣ 📂 Data # Captured and processed signal data ┃ ┣ original_signal.iq ┃ ┣ replayed_signal.iq ┃ ┗ processed_packets.csv ┣ 📜 replay_attack_analysis.py # Analyze replayed vs. original signals ┣ 📜 rolling_code_identification.py # Detect rolling codes & decode bitstream ┣ 📜 signal_data_analysis.py # General signal and packet statistics ┣ 📜 pearson_coefficient.py # Calculate Pearson correlation between signals ┣ 📜 requirements.txt # Python dependencies ┗ 📂 results # Output graphs and analysis results ┣ replay_comparison.png ┣ rolling_code_graph.png ┗ pearson_heatmap.png

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⚙️ Requirements

• Python 3.8+
• RTL-SDR / HackRF or other SDR hardware (for signal capture)
• Libraries: pip install numpy scipy matplotlib pandas bitstring seaborn 🚀 How to Run 1️⃣ Replay Attack Analysis Compare original and replayed key fob signals. python replay_attack_analysis.py --original Data/original_signal.iq --replay Data/replayed_signal.iq --output results/replay_comparison.png 2️⃣ Rolling Code Identification & Bitstream Decoding Detect rolling codes and extract decoded bitstream. python rolling_code_identification.py --input Data/processed_packets.csv --output results/rolling_code_graph.png 3️⃣ Signal & Data Analysis General statistics and visualization. python signal_data_analysis.py --input Data/processed_packets.csv --output results/signal_stats.txt 4️⃣ Pearson Coefficient Analysis Compute correlation between original and replayed signals. python pearson_coefficient.py --original Data/original_signal.iq --replay Data/replayed_signal.iq --output results/pearson_heatmap.png

📊 Methodology Signal Capture – Use SDR hardware to record .iq files.

Replay Attack Analysis – Compare replayed signals against original captures.

Rolling Code Identification – Find changing code segments between transmissions.

Bitstream Decoding – Convert RF captures into binary streams.

Pearson Correlation – Quantify similarity between original and replayed signals.

Visualization – Create plots for presentation & reporting.

Replay Analysis	Rolling Code Visualization	Pearson Correlation

📜 Legal & Ethical Notice Educational and research use only.

Testing without authorization is illegal.

Comply with local RF and cybersecurity laws.

👨‍💻 Author Akshat Pal 🔗 GitHub Profile | akshat4703@gmail.com