A Deep Learning-Based Blockchain Mechanism for Secure Internet of Drones Environment

Singh, Maninderpal; Aujla, Gagangeet Singh; Bali, Rasmeet Singh

Abstract

Drones are equipped with high-vision cameras, advanced sensors, and GPS receivers to deliver diverse services from high altitude thereby creating an airborne network. In this environment, physical things (drones, sensors, etc.,) are controlled using computational algorithms to form a cyber-physical system for the Internet of drones. Although the drones provide manifold benefits still there are many issues (security, privacy, and data integrity) which must be resolved before the usage of drones in smart cyber-physical systems. So, in this paper, a blockchain-based security mechanism for cyber-physical systems is proposed to ensure secure transfer of information among drones. In this mechanism, the miner node is selected using a deep learning-based approach, i.e., a deep Boltzmann machine, using features like computational resources, the available battery power, and flight time of the drone. The proposed mechanism is evaluated based on different performance metrics and the results obtained show the potential benefits of the proposed scheme.

Citation

Singh, M., Aujla, G. S., & Bali, R. S. (2021). A Deep Learning-Based Blockchain Mechanism for Secure Internet of Drones Environment. IEEE Transactions on Intelligent Transportation Systems, 22(7), 4404-4413. https://doi.org/10.1109/tits.2020.2997469

• Journal Article Type: Article
• Acceptance Date: May 21, 2020
• Online Publication Date: Jul 7, 2020
• Publication Date: 2021-07
• Deposit Date: Sep 29, 2020
• Journal: IEEE Transactions on Intelligent Transportation Systems
• Print ISSN: 1524-9050
• Electronic ISSN: 1558-0016
• Publisher: Institute of Electrical and Electronics Engineers
• Peer Reviewed: Peer Reviewed
• Volume: 22
• Issue: 7
• Pages: 4404-4413
• DOI: https://doi.org/10.1109/tits.2020.2997469
• Public URL: https://durham-repository.worktribe.com/output/1255354