Blockchain-based privacy and security model for transactional data in large private networks.

Area of Science:

• Cyberphysical Systems Security
• Network Privacy Architecture
• Blockchain Applications in Networking

Background:

• Cyberphysical systems are integral to modern communication, connecting physical devices within large private networks.
• A critical challenge in establishing these networks is protecting transactional data privacy against sophisticated adversarial exploitation.
• Existing solutions often fall short in providing robust, end-to-end security for sensitive transaction data.

Purpose of the Study:

• To propose a novel privacy-preserving architecture for securing transaction data in large private networks.
• To enhance the security and privacy of user transactional data during transit and node-to-node interactions.
• To improve the efficiency of data encryption and decryption processes within these networks.

Main Methods:

• Implementation of a privacy-preserving architecture integrating digital certificates and RSA-based public key infrastructure.
• Leveraging blockchain technology to ensure data integrity, authenticity, and secure provenance.
• Conducting security and performance analyses to validate the proposed model's effectiveness.

Main Results:

• The proposed model demonstrated a significant increase in encryption speed (approximately 17 times) and decryption speed (4 times).
• An average overall acceleration of 16.5 was achieved, indicating substantial performance improvements.
• Security analysis confirmed the model's ability to safeguard data integrity and provenance during network communications.

Conclusions:

• The developed architecture effectively mitigates transactional data privacy risks in large private networks.
• The integration of blockchain and PKI offers a more secure and efficient solution compared to existing methods.
• The findings support the proposed model's suitability for enhancing security in cyberphysical systems and private networks.