chapter  4
26 Pages

Hardware-primitive-based blockchain for IoT in fog and edge computing

WithUzair Javaid, Muhammad Naveed Aman, Biplab Sikdar

Decentralised and trust-less Internet of things (IoT) network architectures will play a key role in the advancement of edge computing in which data will be processed locally at the site of generation and not in a centralised manner. The need for integrating cloud, fog, and edge computing infrastructures is consistently being highlighted by the requirement of supporting both latency-sensitive and computing-intensive IoT applications. For such an integration, it is indispensable that IoT-based environments and their operation be made secure.

Digital provenance alongside scalability and standardisation are among the key concerns in IoT-based environments such as in smart city, smart grid, and vehicular networks, etc. Because the operation of these environments relies heavily on data processing and sharing, it is important that IoT devices preserve data integrity and transmit data in a secure way. Many IoT devices suffer from impersonation and tampering attacks because of their architectural and computational limitations that are unable to provide an adequate level of security. Their inherent nature of low-processing capability, limited bandwidth, and small memory limits them from using advanced security protocols and from doing computing-intensive tasks. This makes it easier for adversaries to hack these devices and manipulate their data. Hardware-primitive-based blockchain is an attractive candidate that can address these concerns and realise future security attributes for fog and edge computing by providing a transparent and auditable system design.

This chapter introduces establishing digital provenance in IoT-based environments by using physical unclonable functions (PUFs), blockchain, and smart contracts. PUFs provide unique hardware fingerprints to establish provenance, and blockchain provides a decentralised digital ledger which is able to withstand data tampering attacks, thereby preserving data integrity.