Visible to the public Towards data assurance and resilience in IoT using blockchain

TitleTowards data assurance and resilience in IoT using blockchain
Publication TypeConference Paper
Year of Publication2017
AuthorsLiang, X., Zhao, J., Shetty, S., Li, D.
Conference NameMILCOM 2017 - 2017 IEEE Military Communications Conference (MILCOM)
ISBN Number978-1-5386-0595-0
Keywordsauditing, blockchain, blockchain security, Computer architecture, control systems, Date Assurance, Distributed databases, drone, drones, integrity, pubcrawl, reliability, resilience, Scalability, secure communication, security scalability, Servers
Abstract

Data assurance and resilience are crucial security issues in cloud-based IoT applications. With the widespread adoption of drones in IoT scenarios such as warfare, agriculture and delivery, effective solutions to protect data integrity and communications between drones and the control system have been in urgent demand to prevent potential vulnerabilities that may cause heavy losses. To secure drone communication during data collection and transmission, as well as preserve the integrity of collected data, we propose a distributed solution by utilizing blockchain technology along with the traditional cloud server. Instead of registering the drone itself to the blockchain, we anchor the hashed data records collected from drones to the blockchain network and generate a blockchain receipt for each data record stored in the cloud, reducing the burden of moving drones with the limit of battery and process capability while gaining enhanced security guarantee of the data. This paper presents the idea of securing drone data collection and communication in combination with a public blockchain for provisioning data integrity and cloud auditing. The evaluation shows that our system is a reliable and distributed system for drone data assurance and resilience with acceptable overhead and scalability for a large number of drones.

URLhttps://ieeexplore.ieee.org/document/8170858/
DOI10.1109/MILCOM.2017.8170858
Citation Keyliang_towards_2017