Blockchain-Enabled Data Collection and Sharing for Industrial IoT With Deep Reinforcement Learning

• Published in: IEEE transactions on industrial informatics Vol. 15; no. 6; pp. 3516 - 3526
• Main Authors: Liu, Chi Harold, Lin, Qiuxia, Wen, Shilin
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.06.2019; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Blockchain; crowdsourcing; Cryptography; Data collection; Data retrieval; deep reinforcement learning (DRL); Distributed databases; energy efficiency; Energy sources; Industrial applications; Industrial development; industrial Internet of thing; Information sharing; Internet of Things; Machine learning; Reinforcement learning; secure data sharing; Security; Sensors; Task analysis
• ISSN: 1551-3203; 1941-0050
• DOI: 10.1109/TII.2018.2890203

With the rapid development of smart mobile terminals (MTs), various industrial Internet of things (IIoT) applications can fully leverage them to collect and share data for providing certain services. However, two key challenges still remain. One is how to achieve high-quality data collection with limited MT energy resource and sensing range. Another is how to ensure security when sharing and exchanging data among MTs, to prevent possible device failure, network communication failure, malicious users or attackers, etc. To this end, we propose a blockchain-enabled efficient data collection and secure sharing scheme combining Ethereum blockchain and deep reinforcement learning (DRL) to create a reliable and safe environment. In this scheme, DRL is used to achieve the maximum amount of collected data, and the blockchain technology is used to ensure security and reliability of data sharing. Extensive simulation results demonstrate that the proposed scheme can provide higher security level and stronger resistance to attack than a traditional database based data sharing scheme for different levels/types of attacks.