Counterfeiting in the pharmaceutical industry is a major global issue, which causes fatality for hundreds of thousands each year [1]. Counterfeit drugs can cause a further financial burden on the healthcare system as they sometimes worsen patients’ health. They have between 10% and 30%of the global market share in the medical industry due to the ineffectiveness of monitoring agencies [1,2,3,4]. Moreover, for the U.K., this could soon be escalated further by the impact of Brexit, as the transition means that the U.K. will no longer be under the protection of the Falsified Medicine Directive (FMD) [5]. U.K. officers identified over 3 million counterfeit medicines and medical devices valued at over £9 million, with only seven criminals arrested [6], showcasing the effectiveness of the current monitoring system. According to recent investigations, the current pandemic has also helped boost the problem we face. Interpol’s investigation in March 2020 suggests that the sale of medicines and medical products, particularly related to the COVID-19 pandemic, is on the rise, with over 2000 online links advertising false pandemic-related medical items [7] the following operation (Pangea), coordinated by Interpol from 18 to 25 May 2021, resulted in thousands of illegally operating websites being removed [6]. Authors of [8] suggest that the current centralized monitoring systems are managed by a particular set of people with the risk of a single point of failure, e.g., a recent incident of the outage of Facebook services due to unintentional faulty configuration of the centralized servers [9] is a reminder of possible failure point in any centralized systems. The centralized systems are mutable and require a vast majority of trust from the responsible parties for handling such systems to ensure the integrity and ingenuity of the stored data; consequently, it is justifiable to assume that a centralized system is usually an easier target for cyber threats than a decentralized system. Monitoring and enforcing regulations on fighting against counterfeit medicine is costly and time-consuming, particularly for developing countries [5,8,10]. In addition, the lack of transparency throughout the pharmaceutical distribution system, from the manufacturers to the wholesalers, retailers, hospitals, and pharmacies, has been the main drawback of the current solutions [3,4,8]. These factors contribute to the need for scalable, transparent transaction records of the medicines and, at the same time, a secure decentralized monitoring system for pharmaceutical distribution. In contrast, such a system reduces the trust factor between the participants. Hence, this paper tackles some issues related to a decentralized monitoring system. It proposes a solution for a trustless distribution monitoring system to fight against counterfeit drugs using a variation of the zero-knowledge proof protocol (ZKP).

2. Existing Solutions

2.1. RFID and Barcode Technology

Mass serialization using radio frequency identification (RFID) and barcode technology have been used widely for the past few decades in the healthcare industry to track medicines through the supply chain. RFID is more costly to implement than barcode technology, and it is much more effective against cloning and fake identification. This has helped reduction in medication and diagnosis errors in pharmaceuticals [13]. Barcode is a much older technology, and so is its efficiency in product tracking [3,14]. However, the work described by the authors of [3] elaborates on a cheaper manufacturing technique of RFID compared to the past, making RFID a better solution for delivering improved operational performance. The aforementioned technologies are necessary for the identification of packages and complementary for developing an effective monitoring system.

2.2. Holographic Technology

Unique holographic packaging is another solution against counterfeit products. Although it is not impossible to clone such packaging, the manufacturers use holographic technology to ensure the legitimacy of these packages. However, due to reprinting and repackaging by retailers, this method can often be costly and inefficient [8]. Furthermore, it leaves room for errors and malicious intentions.

2.3. The Falsified Medicine Directive (FMD)

The European Council adopts the Falsified Medicine Directive (FMD) to introduce measures to fight medicine falsifications and ensure medicine safety within Europe [15]. This is an example of a centralized monitoring system where the FMD servers control the monitoring for the flow of medicine in Europe. From the end of 2020, the United Kingdom is no longer under the protection of FMD; therefore, an alternative may become necessary for the United Kingdom.

Most or all the existing solutions do not provide a transparent picture across the supply chain. It leads to mistrust, data falsification, un-traceable, inefficient, opaque, and provides an opportunity to manipulate where and when possible. This idea is confirmed by the reports highlighted in the work of [16].

3. Blockchain Solutions

This section consists of the current solutions, research, and studies on blockchain and supply chains in various industries and their benefits.

In addition to cryptocurrencies and non-fungible tokens (NFT), researchers and government bodies notice other advantages to a decentralized ledger. U.S. Food and Drug Administration (FDA) published an announcement to develop an improved track and trace system for the supply chain of medicine. It is set to come into effect in 2023. The new proposed system includes technologies such as blockchain [17]; this shows that the benefits of using blockchain technology are recognized within the government bodies. The distributed ledger increases trust and results in economic efficiencies; established pharmaceutical companies such as Pfizer, Amgen, and Sanofi have been exploring using blockchain to document the testing of new drugs to speed up the creation of new medicines and their delivery to the market. Patientory and Coral Health are also considering allowing patients to control the data stored and track the medicine type and quantity they have received over time, taking advantage of the transparency this technology brings [18,19].

Additionally, other supply chains consider blockchain technology; as an example, Walmart participated in research to use the blockchain system, improving transparency and faster processing in their food supply chain [20]. The authors of [3] introduce the need for blockchain technology in Taiwanese pharmaceuticals by proposing ‘Gcoin’. This suggests that using distributed ledger can help implement a monitoring system that ensures the integrity of the drugs, improves the quality of the products, leading to better security and health of consumers; nevertheless, this paper limits the technicality of the consensus features the system could provide. Similarly, the authors of [21] propose a real-time remote monitoring private system based on the Ethereum protocol that allows physicians to record patients’ up-to-date health history. However, both articles lack the consideration of assuring a genuine supply of products’ history in the medicines’ distribution chain.

One of the implementation decisions to be made is the nature of the transaction environment and the consensus protocol they adopt. The authors of [4] suggest that private blockchains are more secure than the alternative. This way, legitimate participants are granted access to participate on the blockchain. The work of [8] proposes PharmaCrypt, an application tool using Ethereum private blockchain system. The application uses Amazon Web Services (AWS) and smart contracts, and in the model, products can be created and transferred between accounts. Mobile devices running the application can work as a barcode scanner to create new assets assigned with a unique identifier number; this promises implementation of the current technologies in use into an up-to-date supply chain system. The author indicated some scalability issues with their solution and further development requirement. It is argued that private blockchains are not genuinely decentralized as the participating nodes must be authorized to be a part of the network [22]. However, in a distributed system, the nodes are required to be authenticated by an authority (or, in this case, the genesis system); to ensure the integrity of the incoming nodes to the rest of the network.

3.1. Private vs. Public

In 2009, Satoshi Nakamoto implemented the first blockchain as a public ledger for cryptocurrency using the proof of work (PoW) consensus technique [12]. Since then, blockchain technology has been evolving to create immutable chains meeting different criteria. Many blockchain solutions are currently under development to meet different needs that include providing transparency, integrity, traceability, and auditability. Blockchain systems usually fall into four categories: permission/private blockchains, permissionless/public blockchains, consortium blockchains, and hybrid blockchains. A private blockchain is an invite-only type of network. Each node on this type of network gets authorized by a group (or an individual/genesis system) before gaining access rights. There are several use cases of a private chain in supply chain management, global financial trade, retail, healthcare, and more. Permissionless chains are, however, open to join and leave on demand by the public; also referred to as public chains, it is ideal for cryptocurrencies and e-voting systems. A consortium chain is similar to a private blockchain, but the key difference is that it gets governed by a group of entities rather than one. It can be used in similar industries as a private blockchain would. A hybrid blockchain combines public and private features, so it is a blockchain accessible by the public, but a smaller group of authorized nodes do the modifications.

Public blockchain gives the pseudo-anonymity feature to keep the network’s identity unknown [23]. They usually consist of full nodes and simple nodes. Simple nodes can send and receive transactions; it is not necessarily required for a simple node to store the ledger or validate a transaction; in a proof of work (PoW)-based blockchain system, simple nodes are the users of the network. A full node must store the full blockchain, participate in the consensus and validate each block; full nodes in the same PoW network are the miners. A private blockchain network is an invite-only network, where the new nodes go through an authentication through the authority before joining the network. Transactions are usually visible to authorized users, whereas, in a public ledger, transactions are visible by everyone in the network; this increases the data privacy of the transactions in a private blockchain network [24]. Usually, each node in the network uses asymmetric encryption keys for digital signatures and authentication of their identity to the rest of the network. In a public ledger, these asymmetric keys are the primary identifiers of the node [25]. Permissionless or public blockchains are ideal for anyone to join to validate the blocks or create a new transaction; however, scalability is an issue factor due to its availability to the public [26].

Cryptocurrencies and NFT are the popular public blockchain as the public is permitted to participate in block creation and consensus making. Bitcoin and Ethereum are the most famous examples that fall in the same category; they both rely on public verification (miners) of the transactions [27]. Miners in a blockchain network consume much computational power; they require high electricity and hashing power, making them an expensive solution to implement and maintain. According to the work of [28], Bitcoin, which runs on a proof of work consensus, consumes 83.23 TWh of electricity, equivalent to the power consumption of Finland. According to the work of [29], Bitcoin solely uses more electricity than Argentina [28]. For a pharmaceutical distribution system, a private chain is ideal for authorizing and authenticating the nodes entering the network and holding them accountable for their integrity. If a validator attempts an attack on the network, meaning a validator should try to compromise the network with a new set of data or defies integrity, a penalty mechanism slashes the node’s stake and ejects the node from the network; Algorand is an excellent example of proof of stake (PoS) in a distributed network [30] introduces a pure proof of stake (PPoS) protocol and private blockchain, addressing security concerns of such system such as the ’long range attacks’ [31] with forward-secure signature. This protocol mechanism is an example of a ‘consensus’ protocol. The problem arises when the participants with the majority of the stake either become the target to intruders or dictate false information tampering with the integrity and purity of the data input.

3.2. Consensus

From the literature investigated, a consideration of decision-making protocol to increase the network’s trust-based integrity and reliability was unidentified. This section includes some of the relevant consensus protocols adopted by different blockchain technology for block verification and validation process, canvassed, and compares their relevance to the pharmaceutical distribution supply chain.

In real-world, day-to-day interactions, people decide whom to interact with based on their reputation and how much they trust them; similarly, merchants in the market build reputation and trust-based on long-term fair trade between them [32]. In a distributed ledger, the problem arises when nodes in the network need to trust one another on the integrity of the data received. The authors of [33,34,35] demonstrate a zero-knowledge proof protocol (ZKP) where the nodes can agree on the knowledge of data D by proving K, where K is directly relative to D, without revealing the actual data. An application of ZKP is the circuit computations model. A random subset of the encoded version of the data requested from the verifier and the prover provides the subset of the requested information to be verified.

As part of the consensus of the blockchain system, all the participating nodes must agree on the appended block, so another problem that the system needs to address is when the system splits into multiple nodes with different responses in the verification process. The authors of [36,37,38] introduce trust-based consensus protocols with a reputation scoring system; these papers suggest a rating system for the nodes in the network based on their participation in the consensus. An alternate way to calculate a node’s trustworthiness is using the Markov model [39]. The authors of [40] discuss the use of proof of authority (PoA) protocol; the ‘authority’ becomes the final decision maker; however, it seems adrift from the idea of decentralization and also a risk of a single point of failure, since the authority is known to the participating nodes in the network.

An in-depth analysis of pre-existing literature has led to an overview of the blockchain technology and relevant features it can provide before conducting the programming element of the research work presented in this paper. There are suggestions to improve the management of the supply chain through the use of technology [19]. One way to tackle this issue is using blockchain. Using a decentralized ledger reduces operational inefficiencies and increases overall security. The blockchain network can be Byzantine fault-tolerant; this gives full transparency over transactions happening in real-time. Allows participants to monitor the data, which, in the end, concludes to patients receiving genuine products that route back to legitimate manufacturers [41]. The paper aims to adopt variations of the literature covered, such as the work of [35], the ZKP circuit computation model, and the use of the Markov model to make a consensus decision once the system splits into groups with various responses. The paper established the suitability of a private blockchain network environment for a pharmaceutical distribution system, so the nodes are required to go through an authentication process with authority (genesis system).