ABSTRACT Digital twin technology has emerged as a key innovation in digitalization, gaining significant attention for its wide applicability across space and manufacturing industries. Its primary goal is to enable efficient command execution and secure data access, empowering users within a virtual environment. Digital twins support various functions, such as real‐time monitoring, data analysis, and synchronized operations. However, despite their growing adoption, critical issues related to data privacy and security within digital twin systems remain underexplored. To address this, the article introduces an advanced optimization algorithmic technique, ChronologicalFossa Optimization AlgorithmSecure Key Generation (CFOASeckeygen), for generating an optimal key to improve the security and privacy of data stored in a digital twin environment with a blockchain framework. Towards this, different entities, like the twin manager, data owner, database server, and data user, are involved in the authentication process, which is executed by considering different functions, like Exclusive OR (XOR) operations, cryptographic hashing, encryption, and keys. Following this, a secret key is generated using CFOASeckeygen to increase security as well as the privacy of digital twin data. Furthermore, the CFOASeckeygen model demonstrates superior performance, achieving a communication cost of 3007. 556, memory usage of 43. 876 MB, a normalized variance of 0. 885, and a conditional privacy score of 0. 886.
B et al. (Thu,) studied this question.