EntropyX – Quantum-Inspired Cyber Forensics Toolkit

EntropyX is a Python tool that analyzes and visualizes entropy patterns in files to detect hidden encrypted data, obfuscation, and anomalies. It combines classical Shannon entropy with quantum-inspired estimation, supports chunk-based and sliding window analysis, provides interactive plots and heatmaps, and exports results for forensic reporting. Fully offline and lightweight, EntropyX bridges quantum concepts and digital forensics in a practical, hands-on toolkit

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📘 Table of Contents

1. Overview
2. Features
3. Quantum Simulation
4. Visualization
5. Use Case: Cyber Forensics
6. Technologies Used
7. Installation & Setup
8. File Structure
9. Screenshots
10. Forensic Value
11. Future Improvements
12. Author
13. License

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🔍 Project Overview

EntropyX is a Python + Streamlit toolkit for *cyber forensic investigations, designed to profile *entropy distribution across files using both classical and quantum-inspired methods.

It helps detect suspicious file regions that may indicate:

• Encryption or compression
• Obfuscation or steganography
• Data tampering or hidden payloads

🧠 Built for education and demonstration — showing how quantum-inspired algorithms can enhance modern digital forensics.

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🚀 Features

✅ Core Functionality

• Upload any binary or text file and scan for entropy anomalies
• Chunk-based entropy analysis with adjustable segment size
• Entropy estimation modes:
  • 📘 Classical Shannon Entropy
  • 🧪 Quantum-inspired Entropy Proxy (Qiskit or fallback mode)
• 📊 Interactive line plots and heatmaps
• ⚠ Anomaly detection: highlights entropy spikes
• 💾 Save/load profiles in SQLite database
• 📤 Export results as JSON forensic reports

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🧪 Quantum Simulation

When available, Qiskit powers a simulated quantum backend that:

• Encodes file segments into qubit superpositions
• Applies Hadamard transformations to extract interference-based entropy
• Produces a quantum-derived entropy signature for each file region

🔁 If Qiskit isn’t installed, EntropyX automatically falls back to a pseudo-quantum estimator using randomized classical approximations.

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📊 Visualization

• Comparative entropy line plot (classical vs quantum)
• Heatmap visualization of entropy across file regions
• Adjustable thresholds for custom anomaly sensitivity

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🔄 Sliding Window Analysis

• Supports sliding window sampling (overlapping chunks)
• Detects subtle, localized entropy variations
• Ideal for identifying partial encryptions or hidden payloads

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💼 Use Case: Cyber Forensics

EntropyX assists analysts in identifying and visualizing hidden data zones in digital evidence.

Scenario	Application
🔐 Hidden Payloads	Detect encrypted or obfuscated file regions
🦠 Malware Analysis	Locate polymorphic or packed binaries
🧩 Data Tampering	Highlight irregular entropy distributions
🧾 Evidence Profiling	Export entropy maps for forensic documentation

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🧠 Technologies Used

Technology	Purpose
Python	Core language
Streamlit	Web-based interface
Qiskit	Quantum circuit simulator (optional)
Numpy	Numerical computation
Matplotlib	Entropy visualization
SQLite	Persistent profile database
JSON	Forensic export format

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🛠 Installation & Setup

🔧 Requirements

• Python 3.8+
• Virtual environment recommended

📦 Install Dependencies

pip install -r requirements.txt

If issues arise with Qiskit or Numpy:

pip install --only-binary=:all: numpy
pip install qiskit-terra qiskit-aer

▶ Run EntropyX

streamlit run app.py

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🗂 File Structure

EntropyX/
├── app.py                # Streamlit UI
├── quantum_entropy.py    # Entropy analysis logic
├── profiles.db           # SQLite database (auto-created)
├── requirements.txt
└── README.md

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🛡 Forensic Value

Feature	Benefit
Quantum Proxy Entropy	Simulated next-gen forensic analysis
Sliding Window Sampling	Detects fine-grained payloads
Local Database	Case management and storage
JSON Export	Portable, auditable evidence
Offline Operation	100% local and secure

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🧭 Future Improvements

• 🔍 Integrate YARA pattern matching
• 🧠 Connect to real IBM Quantum hardware
• 🧠 Add memory dump analysis support
• 📝 Include chain-of-custody metadata
• 📄 Auto-generate PDF forensic reports

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👨‍💻 Author

Adhiyaman Babu

Cybersecurity & Quantum Computing Enthusiast 🌐 GitHub · 💼 LinkedIn

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📜 License

This project is open source under the MIT License.