Blockchain in Edge - Cloud Computing Continuum
Name
Iwada Eja Bassey
Abstract
In the era of Edge Computing, Internet of Things(IoT) devices connect and communicate to create a network of objects that can collect information from the environment without human intervention. While the IoT offers many benefits, it also poses several cybersecu- rity risks, including the lack of detection of malicious IoT sensors, weak authorization, and authentication protocols, and insecure management of data received from IoT devices. Developing new solutions to enhance IoT sensors’ security to address these issues is crucial. One crucial challenge that requires attention is the secure management and storage of data collected from IoT devices at the Edge. Many existing solutions rely on centralized systems vulnerable to tampering and must provide reliable data traceability records. To address this challenge, this thesis proposes a blockchain-based architecture for securing and managing data collected from IoT devices. By leveraging blockchain technology, we create a distributed data storage architecture that eliminates the need for centralized network topologies. This approach offers several advantages, including immutability, decentralization, distributivity, enhanced security, transparency, instant traceability, and increased efficiency through automation. Our results demonstrate that this proposed architecture provides a high level of performance and can be used as a scalable, massive data storage solution for IoT devices using blockchain technologies. One significant advantage of this approach is that new IoT sensors can quickly be enrolled and unenrolled in our architecture without retrofitting. Our system does not depend on any specific communication protocol and can be applied to any IoT application. In summary, our proposed architecture provides a robust and secure solution for managing and storing data collected from IoT devices, thus enhancing the overall security of the IoT devices in the Edge.
Graduation Thesis language
English
Graduation Thesis type
Master - Computer Science
Supervisor(s)
Chinmaya Kumar Dehury, Mubashar Iqbal
Defence year
2023