數位孿生(DT)技術對於工業4.0時代的智慧工廠至關重要，它將實體世界與數位模型連接起來以模擬現實世界的行為。DT可以提高製造業的生產效率和產品質量，使安全保護對於防止資料外洩、保護隱私和提高系統彈性至關重要。本研究參考NIST隱私框架和NIST IR 8496指南，基於區塊鏈和容器技術，為製造業提出了一種新穎的數位孿生安全保護方案(DTSPS)。DTSPS包括以下機制：（1)資料安全保護機制：透過標準化、清洗、將資料導入區塊鏈，確保資料的完整性和準確性；（2）資料隱私分級與隔離機制：根據NIST IR 8496對資料敏感度進行分級，採用平行傳輸技術，在平衡效率和安全性的同時防止隱私外洩；（3）雙鏈數據完整性監控機制：利用公有鏈和私有鏈監控數據完整性，隔離數據，防止篡改和洩露；（4）區塊鏈節點故障復原機制：利用節點備份並在私鏈上記錄雜湊表，在災難或攻擊發生後快速自動恢復資料儲存系統，增強安全彈性。實驗結果顯示，本論文所提出的DTSPS的綜合安全指數為0.9263，超過了現有文獻報告的0.6893，顯示增強了數位孿生的資料保護。 DTSPS將平均恢復時間(MTTR)從135分鐘減少到10分鐘，恢復時間變異性(RTV)從20分鐘減少到2分鐘，從而提高了系統的彈性。這些發現為製造業開發數位孿生安全解決方案提供了寶貴的參考。

Digital Twin (DT) technology is crucial for smart factories in the Industry 4.0 era, connecting the physical world with digital models to simulate real-world behaviors. DT can enhance production efficiency and product quality in manufacturing, making security protection vital to prevent data breaches, protect privacy, and improve system resilience. This study proposes a novel digital twin security protection scheme (DTSPS) for the manufacturing industry, based on blockchain and container technology, using NIST Privacy Framework and NIST IR 8496 guidelines. The DTSPS includes the following mechanisms: (1) Data security protection mechanism: It ensures data integrity and accuracy by standardizing, cleaning, and importing data into the blockchain; (2) Data privacy classification and isolation mechanism: It classifies data sensitivity according to NIST IR 8496 and uses parallel transmission technology to prevent privacy leaks while balancing efficiency and security; (3) Dual-chain data integrity monitoring mechanism: It leverages public and private blockchains to monitor data integrity and isolate data, preventing tampering and leakage; (4) Blockchain node failure-recovery mechanism: It uses node backup and record hash tables on the private chain to quickly and automatically restore the data storage system, after a disaster or attach, enhancing security resilience. Experimental results show that the proposed DTSPS achieves a comprehensive security index of 0.9263, surpassing the 0.6893 reported in existing literature, indicating enhanced data protection for digital twins. DTSPS reduces the mean time to recovery (MTTR) from 135 minutes to 10 minutes and recovery time variability (RTV) from 20 minutes to 2 minutes, improving the system resilience. These findings offer valuable guidance for the manufacturing industry in developing digital twin security solutions.

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