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A Blockchain-Enabled Drone-Facilitated Home Quarantine Supervision Scheme in Pandemic Situations
Abstract
Pandemics are very burdensome for every country in terms of health and economy. Technology is needed to come forward to lessen the burden. As finding cure instantly is not always possible, prevention method can be adopted to reduce the damages. Among the methods, home quarantine (HQ) can be beneficial. However, maintaining HQ is very difficult, especially in remote areas where network connectivity is very limited. Drones, dew computing, and blockchain are emerging technologies which can assist in reducing damages. This paper presents a blockchain enabled home quarantine supervision scheme in which patients are monitored using drones. A lightweight computation environment is established to assist the drone. A proof of concept is established to demonstrate the feasibility.
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This paper presents a blockchain enabled secure data acquisition scheme utilizing an Unmanned Aerial Vehicle (UAV) swarm where data are collected from internet of things (IoT) devices and subsequently, forwarded to the nearest server through the UAV swarm. Before initiating data acquisition, the UAV swarm shares a shared key with IoT devices in order to maintain communications. However, prior to transmitting data, IoT devices encrypt the data and forward it to the UAV swarm. Upon receiving the data, the UAV swarm implements a two-phase validation utilizing the π-hash bloom filter and the digital signature algorithm to validate the sender; in addition, prior to forwarding data to the nearest server, it performs encryption. However, before adding data in blockchain, consent from all validators is required. Finally, the data are stored in blockchain with the approval of validators. A security analysis is performed to demonstrate the feasibility of the proposed scheme. Finally, the effectiveness of the proposed scheme is manifested through implementation and simulation. The security analysis and the performance results show that UAV assist IoT devices both in terms of connectivity and energy consumption, and provides security against the threats mentioned in the paper.
Edge-of-Things (EoT) enables the seamless transfer of services, storage and data processing from the Cloud layer to Edge devices in a large-scale distributed Internet of Things (IoT) ecosystems (e.g., Industrial systems). This transition raises the privacy and security concerns in the EoT paradigm distributed at different layers. Intrusion detection systems are implemented in EoT ecosystems to protect the underlying resources from attackers. However, the current intrusion detection systems are not intelligent enough to control the false alarms, which significantly lower the reliability and add to the analysis burden on the intrusion detection systems. In this article, we present a DaaS, Dew Computing as a Service for intelligent intrusion detection in EoT ecosystems. In DaaS, a deep learning-based classifier is used to design an intelligent alarm filtration mechanism. In this mechanism, the filtration accuracy is improved (or sustained) by using deep belief networks. In the past, the cloud-based techniques have been applied for offloading the EoT tasks, which increases the middle layer burden and raises the communication delay. Here, we introduce the dew computing features which are used to design the smart false alarm reduction system. DaaS, when experimented in a simulated environment, reflects lower response time to process the data in the EoT ecosystem. The revamped DBN model achieved the classification accuracy up to 95%. Moreover, it depicts a 60% improvement in the latency and 35% workload reduction of the cloud servers as compared to Edge intrusion detection system.
Internet of things (IoT), mobile edge computing (MEC), and unmanned aerial vehicle (UAV) have attracted significant attention in both industry and academic research. By consolidating these technologies, IoT can be facilitated with improved connectivity, better data transmission, energy saving, and other advantages. However, the communication between these entities is subject to potential cyber threats. In addition, the integrity of the data must be maintained after storing into local storage. Blockchain is a data structure that supports features like pseudonymity, data integrity etc. This paper represents a blockchain based data acquisition process in which information is gathered from IoTs using UAV as a relay and is securely kept in blockchain at MEC server. In the proposed scheme, data are encrypted prior to transfer to MEC server with the assistance of a UAV. Upon receiving the data, MEC server validates the data and the identity of the sender. Successful validation is followed by stocking of the data into blockchain, subsequent to obtaining consent from the validators. Security analysis is conducted in order to show the feasibility of the proposed secure scheme. Finally, the performance of the proposed scheme is analyzed via simulation and implementation.
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