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Intelligent manufacturing security model based on improved blockchain.
Xu, Jia He; Tian, Yuan; Ma, Ting Huai; Al-Nabhan, Najla.
Affiliation
  • Xu JH; School of Automation, Southeast University, Nanjing 211189, China.
  • Tian Y; Nanjing Institute of Technology, Nanjing 211167, China.
  • Ma TH; Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Al-Nabhan N; Department of Computer Science, King Saud University, Saudi Arabia.
Math Biosci Eng ; 17(5): 5633-5650, 2020 08 24.
Article in En | MEDLINE | ID: mdl-33120570
ABSTRACT
The Industrial Internet of Things (IIoT) plays an important role in the development of smart factories. However, the existing IIoT systems are prone to suffering from single points of failure and unable to provide stable service. Meanwhile, with the increase of node scale and network quantity, the maintenance cost presents to be higher. Such a disadvantage can be effectively compensated by the features such as security, privacy, non-tamperability and distributed deployment supported by the blockchain. In this paper, first, an intelligent manufacturing security model based on blockchain was proposed. Due to the high power consumption and low throughput of the traditional blockchain, IoT devices with limited power consumption can not work independently. Therefore, in this paper, a new Merkle Patricia tree (MPT) was adopted to extend the blockchain structure and provide fast query of node status. Second, since the MPT does not support concurrent operation and the data operation performance deteriorates with high data volume, a lock-free concurrent and cache-based Merkle Patricia tree was proposed (CMPT) to support lock-free concurrent data operation, which can improve the data operation efficiency in multi-core system. The experimental results indicate that, compared with the original MPT, the CMPT proposed in this paper effectively reduced the time complexity of data insertion and data query and improved the speed of block construction and data query.
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Math Biosci Eng Year: 2020 Document type: Article Affiliation country: China

Full text: 1 Collection: 01-internacional Database: MEDLINE Type of study: Prognostic_studies Language: En Journal: Math Biosci Eng Year: 2020 Document type: Article Affiliation country: China