Data security sharing model based on privacy protection for blockchain‐enabled industrial Internet of Things

International Journal of Intelligent SystemsVolume 36, Issue 1 p. 94-111 RESEARCH ARTICLE Data security sharing model based on privacy protection for blockchain-enabled industrial Internet of Things Qikun Zhang, Qikun Zhang School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorYongjiao Li, Yongjiao Li School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorRuifang Wang, Ruifang Wang School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorLu Liu, Lu Liu School of Computer Science and Technology, Beijing Institute of Technology, Beijing, ChinaSearch for more papers by this authorYu-an Tan, Yu-an Tan School of Computer Science and Technology, Beijing Institute of Technology, Beijing, ChinaSearch for more papers by this authorJingjing Hu, Corresponding Author Jingjing Hu hujingjing@bit.edu.cn School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China Correspondence Jingjing Hu, School of Computer Science and Technology, Beijing Institute of Technology, 100081 Beijing, China. Email: hujingjing@bit.edu.cnSearch for more papers by this author Qikun Zhang, Qikun Zhang School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorYongjiao Li, Yongjiao Li School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorRuifang Wang, Ruifang Wang School of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou, ChinaSearch for more papers by this authorLu Liu, Lu Liu School of Computer Science and Technology, Beijing Institute of Technology, Beijing, ChinaSearch for more papers by this authorYu-an Tan, Yu-an Tan School of Computer Science and Technology, Beijing Institute of Technology, Beijing, ChinaSearch for more papers by this authorJingjing Hu, Corresponding Author Jingjing Hu hujingjing@bit.edu.cn School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China Correspondence Jingjing Hu, School of Computer Science and Technology, Beijing Institute of Technology, 100081 Beijing, China. Email: hujingjing@bit.edu.cnSearch for more papers by this author First published: 07 October 2020 https://doi.org/10.1002/int.22293Citations: 9Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat 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. Citing Literature Volume36, Issue1January 2021Pages 94-111 RelatedInformation