TY - JOUR
T1 - Blockchain-based secure delivery of medical supplies using drones
AU - Cheema, Muhammad Asaad
AU - Ansari, Rafay Iqbal
AU - Ashraf, Nouman
AU - Hassan, Syed Ali
AU - Qureshi, Hassaan Khaliq
AU - Bashir, Ali Kashif
AU - Politis, Christos
N1 - Funding Information:
Hassaan Khaliq Qureshi completed his European Union’s (EU) Erasmus Mundus Post Doctoral Fellowship from Frederick University, Cyprus. He received his Ph.D. degree in Electrical Engineering from City, University of London, England in 2011. Earlier, he received the M.Sc degree in Electrical Engineering with a first-class honors from Blekinge Institute of Technology, Sweden in 2006. He is a Senior member of Institute of Electrical and Electronics Engineers (IEEE). He remained Research Assistant in Technical University of Dresden and worked on European Union OPERA project. He is also a recipient of EU Erasmus Mundus staff research mobility under STRONG TIES program. He is currently working as an Associate Professor in NUST, Pakistan. His main research interests include wireless networks, blockchains, Internet of Things (IOTs), Network Intrusion Detection Systems, and energy provisioning issues for infrastructure-less networks.
Publisher Copyright:
© 2021
PY - 2022/2/26
Y1 - 2022/2/26
N2 - The advantages provided by the drones with regards to three dimensional mobility and ease of deployment makes them a viable candidate for 5G and beyond (B5G) networks. Significant amount of research has been conducted on the aspect of networking for using drones as base stations to provide different services. In this work, we deviate from the traditional use of drones to provide connectivity and explore the delivery of products through drones in the context of maintaining social distancing. However, drone delivery process for critical applications such as delivering medical supplies is vulnerable to attacks such as impersonation attacks. The security of drone operation is important to save the users from any breaches that can lead to financial and physical losses. To cope with these security issues and to make the delivery process transparent, we propose a blockchain-based drone delivery system that registers and authenticates the participating entities including products (medical supplies), warehouse (medical centers) and drones. To this end, we utilize Ethereum platform for implementation of blockchain and smart contract and we present an analysis of different factors that influence the authentication process in terms of time and the number of transactions. Furthermore, to make the communication of a drone with command and control center more secure and robust, we use machine learning (ML)-based intrusion detection system.
AB - The advantages provided by the drones with regards to three dimensional mobility and ease of deployment makes them a viable candidate for 5G and beyond (B5G) networks. Significant amount of research has been conducted on the aspect of networking for using drones as base stations to provide different services. In this work, we deviate from the traditional use of drones to provide connectivity and explore the delivery of products through drones in the context of maintaining social distancing. However, drone delivery process for critical applications such as delivering medical supplies is vulnerable to attacks such as impersonation attacks. The security of drone operation is important to save the users from any breaches that can lead to financial and physical losses. To cope with these security issues and to make the delivery process transparent, we propose a blockchain-based drone delivery system that registers and authenticates the participating entities including products (medical supplies), warehouse (medical centers) and drones. To this end, we utilize Ethereum platform for implementation of blockchain and smart contract and we present an analysis of different factors that influence the authentication process in terms of time and the number of transactions. Furthermore, to make the communication of a drone with command and control center more secure and robust, we use machine learning (ML)-based intrusion detection system.
KW - Blockchain
KW - Fifth generation (5G) and beyond
KW - Machine learning
KW - Unmanned aerial vehicles
UR - http://www.scopus.com/inward/record.url?scp=85122543779&partnerID=8YFLogxK
U2 - 10.1016/j.comnet.2021.108706
DO - 10.1016/j.comnet.2021.108706
M3 - Article
AN - SCOPUS:85122543779
SN - 1389-1286
VL - 204
JO - Computer Networks
JF - Computer Networks
M1 - 108706
ER -