Review of the Blockchain Technology and Consensus Algorithms for IoT-Based Banking

Review of the Blockchain Technology and Consensus Algorithms for IoT-Based Banking

DOI: 10.4018/978-1-6684-4176-3.ch002
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The internet of things (IoT) is a global network that connects devices and people, yet it still confronts various challenges. This chapter explores the challenges banks face and how blockchain technology (integrated with IoT devices) can help address them. The chapter has also conducted a review of the different consensus mechanisms employed by the blockchain systems to find out which consensus method should be deployed by IoT-based banks. The underlying consensus method was first created for permissionless blockchain on a trustless network model using proof-of-work, which is a mathematical challenge that demands a lot of computing power. The findings of the study revealed that considering the regulatory requirements such as permissioned blockchains are best suitable for banks due to know your client (KYC) and anti-money laundering (AML) regulatory requirements. Additionally, for such a blockchain network, the practical byzantine fault tolerance (PBFT) and proof of authority (PoA) consensus methods ensure business resiliency.
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Banking and financial services organizations are the backbone of many countries' economic prosperity, and information technology (IT) aids in the management and scaling of services for banking institutions. Knowledge and information processing are the lifeblood of the financial industry. Products are developed, promoted, and distributed via IT systems and applications. Because IT drives all economic activity, an efficient banking system will allow money to move faster, resulting in increased growth and more substantial balance sheets, contributing to economic growth. Digital account opening; application programming interfaces (APIs); video collaboration, peer-to-peer (P2P) payments; and cloud computing are the top five technologies used by banks nowadays. Moreover, retail banking, business, and corporate banking, and investment banking are the three primary categories of banking services (Ramalingam & Venkatesan, 2019).

  • Retail banking- Provides savings, deposits, and loans to individual consumers.

  • Business and corporate banking- Provides current accounts, payments, cash management, trade finance, guarantees, and foreign exchange (FOREX) services to small, medium, and large businesses.

  • Investment banking- Advisory, investment research, brokerage, mergers & acquisitions, and wealth management are all examples of investment banking services.

Banks rely on IT infrastructure to handle their own data processing and link to their various ATM/POS terminals. Retail banks use consumer-facing ATM/POS devices as edge data interfaces to collect multiple forms of banking customer data. The IT infrastructure of a bank is made up of a mix of hardware and software-based systems that store, process, and communicate banking-related data. Branch connectivity is available 24 hours a day, seven days a week, and any downtime is unacceptable. Large data centers can accommodate various databases and software applications for financial products. With the Internet of Things (IoT) power, digital banking brings the above infrastructure closer to acquiring client data, and ATM/POS terminals/mobile banking are evolving. For instance, IoT-based video capturing devices might be used to collect data on customer experience in retail banking and open up new avenues for improvement.

While the big banks are aggressively innovating in many areas to combat competition from so-called “challenger” banks and fintech start-ups, they have mostly left the IoT to other industries, such as retail and manufacturing. Furthermore, the present IoT architecture is based on the server/client model, which is a centralized concept (Atlam et al., 2018). In this arrangement, all devices cannot communicate with one another and must instead communicate through a centralized gateway. For many years, the centralized model has been used to link a wide range of computing devices, and it will continue to support small-scale IoT networks in the future, but it will not be able to meet the needs to expand the IoT system. In addition, data manipulation is a risk with the centralized architecture. However, collecting data in real-time does not guarantee that it is put to excellent and appropriate use. In contrast, payments, enhanced operability (to allow open banking), and better mobile services are essential for banking organizations to survive the fintech competition. Many of these difficulties could be solved with a decentralized IoT solution. Blockchain is one of the most widely used decentralization techniques (Qian et al., 2018). In this context, this chapter focuses on ‘how blockchain can address various challenges faced by the banks and what consensus algorithms should be adopted to implement a IoT-based banking system.’

The remainder of this chapter is divided into the following sections. First, the background on IoT and blockchain is covered in Section 2. Section 3 highlights the primary challenges that banks are now facing and how blockchain could help solve these issues and several consensus techniques are discussed in Section 4. Finally, section 5 discusses the application of consensus algorithms in IoT-based banking, while section 6 investigates potential study discrepancies and suggestions for improvement before section 7 concludes.


Several papers have looked into using a blockchain system in the IoT. This chapter will discuss the existing work in this area to find the research gap.

Key Terms in this Chapter

Nonce: A number or value that can only be used once is referred to as a nonce. Nonces are frequently employed in cryptographic hash algorithms and authentication procedures.

Node: Nodes are network stakeholders and equipment that have been permitted to maintain track of the distributed ledger and act as communication hubs for various network tasks.

Distributed ledger: A distributed ledger is a record of consensus that includes a cryptographic audit trail that nodes maintain and validate. It might be either decentralized or centralized in nature.

Consensus Algorithms: A consensus algorithm allows distributed processes or systems to agree on a single data value in computer science.

Merkle Tree: In computer science, Merkle trees, also known as Binary hash trees, are a common type of data structure.

Permissioned Blockchain: Permissioned blockchains are distributed ledgers that are not open to the public.

Smart Contract: A self-executing contract in which the conditions of the buyer-seller agreement are put directly into lines of code is called a smart contract.

Peer-to-peer Network: Peer-to-peer networking is a distributed application architecture in which jobs or workloads are divided across peers.

Internet of Things: The internet of things (IoT) is a collection of interconnected devices that are connected to a network and/or to one another and exchange data without requiring human-machine interaction.

Public-Key Cryptography: A combination of keys known as a public key and a private key is associated with an entity that needs to authenticate or sign or encrypt data using public-key cryptography.

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