4.7 Article

Efficient and Secure Data Sharing for 5G Flying Drones: A Blockchain-Enabled Approach

Journal

IEEE NETWORK
Volume 35, Issue 1, Pages 130-137

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/MNET.011.2000223

Keywords

Computational modeling; Smart contracts; Authentication; Public key cryptography; Data models; Encryption; Drones

Funding

  1. National Natural Science Foundation of China [61373163]
  2. Japan Society for the Promotion of Science (JSPS) [JP18K18044]

Ask authors/readers for more resources

This study proposes a secure data sharing model for flying drones in 5G environment, utilizing blockchain and ABE technology for authentication and data security. The model incorporates smart contracts, public key cryptography, and distributed ledger for authentication and security audit. Furthermore, the ABEM-POC model and parallel computation method significantly improve the speed of outsourced encryption and decryption.
The drones open and untrusted environment may create problems for authentication and data sharing. To address this issue, we propose a blockchain-enabled efficient and secure data sharing model for 5G flying drones. In this model, blockchain and attribute-based encryption (ABE) are applied to ensure the security of instruction issues and data sharing. The authentication mechanism in the model employs a smart contract for authentication and access control, public key cryptography for providing accounts and ensuring accounts security, and a distributed ledger for security audit. In addition, to speed up out-sourced computations and reduce electricity consumption, an ABE model with parallel outsourced computation (ABEM-POC) is constructed, and a generic parallel computation method for ABE is proposed. The analysis of the experimental results shows that parallel computation significantly improves the speed of outsourced encryption and decryption compared to serial computation.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.7
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available