Blockchain-based cyber-security trust model with multi-risk protection scheme for secure data transmission in cloud computing

Blockchain-based cyber-security trust model with multi-risk protection scheme for secure data transmission in cloud computing

연구 분야: Cryptography

학회: Cluster Computing

The rise of cloud computing has transformed the way data is stored and managed, yet it has also brought about major security issues, especially concerning the secure transfer of data within cloud systems. In response to these challenges, this research develops a comprehensive cyber-security trust model that provides multi-risk protection for secure data transmission in cloud computing, ensuring the highest level of privacy and data security. This innovative approach aims to ensure the secure transmission of data in cloud computing while harnessing the combined strengths of Quantum Key Distribution (QKD) and Advanced Encryption Algorithm. As cloud environments become integral to modern business operations, safeguarding data against a multitude of security risks, including traditional and emerging threats, is paramount. The Cyber-Security Trust Model leverages blockchain to establish a transparent and tamper-resistant ledger of all data transactions within the cloud. This blockchain layer enhances data integrity, auditability, and traceability while also providing a decentralized and trust-based framework for authentication and authorization. The Multi-Risk Protection Model incorporates both Quantum Key Distribution (QKD) and a Modified Advanced Encryption Standard (MAES) to offer multi-layered defence mechanisms. Through rigorous testing and analysis, this study demonstrates the feasibility and effectiveness of the proposed Cyber-Security Trust Model with a Merkle tree-based solution for data integrity verification. It makes a significant impact on the field of secure data transmission in cloud computing by providing strong protection against a constantly changing set of security threats. MATLAB is employed to conduct rigorous experiments, analyse results, and validate the model’s performance in various cloud computing scenarios. The findings of the proposed study show the proposed method, combining Quantum Key Distribution (QKD) and Modified AES (MAES), stands out with exceptional performance, featuring encryption and decryption times of 2.25ms and 1.071ms, respectively. The proposed system outperforms all others, boasting an impressive accuracy rate of 99.84%. This research signifies a ground-breaking advancement in cloud computing security, addressing a spectrum of traditional and emerging threats through a multi-risk protection model incorporating Quantum Key Distribution (QKD) and MAES while demonstrating exceptional performance in rigorous experiments.