Data security sharing model based on privacy protection for blockchain‐enabled industrial Internet of Things
Qikun Zhang, Yongjiao Li, Ruifang Wang, Lu Liu, Yu‐an Tan, Jingjing Hu
Abstract
With the widespread application of Industrial Internet of Things (IIoT) technology in the industry, the security threats are also increasing. To ensure the safe sharing of resources in IIoT, this paper proposes a data security sharing model based on privacy protection (DSS-PP) for blockchain-enabled IIoT. Compared with previous works, DSS-PP has obvious advantages in several important aspects: (1) In the process of identity authentication, it protects users' personal information by using authentication technology with hidden attributes; (2) the encrypted shared resources are stored in off-chain database of the blockchain, while only the ciphertext index information is stored in the block. It reduces the storage load of the blockchain; (3) it uses blockchain logging technology to trace and account for illegal access. Under the hardness assumption of Inverse Computational Diffe–Hellman (ICDH) problem, this model is proven to be correct and safe. Through the analysis of performance, DSS-PP has better performance than the referred works.