Next-Generation, Quantum-Resistant Cryptographic Toolkit
GPU-accelerated AES, post-quantum Dilithium/Kyber, Double Ratchet secure messaging, Rust P2P networking, JWT authentication, Azure cloud integration, and more.
Optimized for high-throughput and future-proof security applications.
- Quantum-Resistant Algorithms: Integrates NIST post-quantum standards like Dilithium & Kyber for robust digital signatures and key exchange.
- GPU Acceleration: Leverages CUDA and Rust for blazing-fast AES and compression suitable for large data and high-performance needs.
- End-to-End Secure Messaging: Implements Double Ratchet for modern, forward-secret communication protocols.
- Multi-Language: Python (main logic), CUDA (GPU), Rust (networking & low-level crypto), C++, and Jupyter Notebooks for demos.
- Cloud-Ready: Azure integration and JWT-based authentication for scalable, secure deployments.
- P2P Networking: Rust-powered peer-to-peer stack for decentralized, encrypted communication.
- API-Ready: Designed to integrate with FastAPI for rapid development of secure services.
- Extensive Testing & Notebooks: Jupyter and JSON utilities for testing, validating, and demoing cryptographic routines.
| Folder | Description | Technologies |
|---|---|---|
AesRust/ |
High-speed AES encryption using Rust and GPU for secure and efficient data protection. | Rust, CUDA |
Azure/ |
Secure integration modules for Microsoft Azure cloud services. | Python |
Dilithium_ECDH_kyber_signature/ |
NIST PQC: Dilithium (signatures), Kyber (key exchange), and ECDH implementations for quantum-safe operations. | Python, C++, Rust |
Double_rachet/ |
Double Ratchet Algorithm for forward-secret, end-to-end encrypted messaging protocols. | Python |
Dumy_data_tester_json/ |
Utilities and sample JSON data for encryption and decryption testing. | Python, JSON |
GPU_Encryption/ |
CUDA-powered encryption modules for high-throughput, parallel data processing. | CUDA, Python |
GPU_compression/ |
GPU-accelerated data compression utilities to maximize storage and transmission efficiency. | CUDA |
Jwt/ |
JWT-based authentication and authorization modules. | Python |
P2P_Rust/ |
Peer-to-peer networking stack for decentralized, secure communication. | Rust |
Q.K.D/ |
Q.K.D implementation + quantum safe | Python |
- Python 3.9+
- Rust 1.73+
- CUDA 12.1+
- C++17
- FastAPI (latest)
- Jupyter Notebook
- Azure SDKs
- JSON Web Token (JWT)
- OpenSSL, PyCryptodome, rust-crypto
- Hybrid Cryptography: Combine classical and quantum-safe primitives seamlessly.
- Performance-Oriented: Designed for large-scale, latency-sensitive, and throughput-intensive environments.
- Security Best Practices: Modern cryptographic standards, forward secrecy, and robust authentication.
- Cloud & Edge Ready: Easily integrate with cloud platforms and IoT/edge devices.
- Continuous Integration: Automated CI for all pushes and pull requests.
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Clone the Repository
git clone https://github.com/thearpankumar/Encrypt5_SecurityProtocols.git cd Encrypt5_SecurityProtocols -
Explore Each Module
- Each folder contains a README or code comments for setup and usage.
- Jupyter Notebooks provide hands-on demonstrations and experiments.
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Setup Dependencies
- Most modules require Python 3.9+, CUDA-enabled GPU, and the Rust toolchain.
- See individual module instructions for environment setup.
- Quantum-Ready Secure Communications: Future-proof your messaging and networking.
- Cloud Security: Integrate robust cryptography into Azure and other cloud workflows.
- High-Performance Data Protection: Encrypt and compress data at speed for big data and IoT.
- Research & Prototyping: Use as a foundation for cryptographic research, teaching, or rapid prototyping.
- Each folder contains example scripts and usage notes.
- For advanced usage and API references, see docs/ or code comments.
Contributions are welcome!
For bug reports, feature requests, or discussions, please open an issue or pull request.
This project is licensed under the MIT License.
See LICENSE for full details.
- NIST PQC Project
- OpenSSL, PyCryptodome, rust-crypto
- Signal Protocol & Double Ratchet paper
- CUDA and NVIDIA for GPU acceleration
Built with passion by thearpankumar and contributors.