The adoption of industrial facilities using information and communication systems to support dependable production has given rise to the Industrial Internet of Things (IIoT). With the aid of IoT and intelligent computing, automation, self-sufficient processing, and computing capabilities are implemented for smart industries1. Through the management layer, the fieldprimary blockchain network implements a layer carries out many duties that support production and customer replies in traditional industry operations2.
Industries are now equipped to meet their users’ growing demands and productivity requirements, thanks to IIoT. Recent developments in robotic and autonomous machines take the place of manual or human-intervened procedures. The potential of machine-oriented jobs to aggregate, analyze and enhance data handling practices and customer replies.
Utilizing pervasive systems, ubiquitous access, distribution of resources, distributing automation, and self-dependent computation are made possible. Infrastructure and applications are made available as amenities in the cloud ecosystem. Data visualization tools, mathematical frameworks, people, applications, intelligent computing machines, and IoT can all work together in the cloud.
With the help of many automated systems and communication methods, such a diversified platform can improve customer service. The IoT has enormous potential to enhance the features and capabilities of any service it provides or supports, regardless of the use case. An additional dimension of difficulties will arise because of current use cases and near future ones.
Centralized data storage is a big obstacle. The existing storage mechanism in IoT system implementations, the quantity of data gathered in one place, and the number of IoT devices all go hand in hand. Concerns about data ownership and administration will arise because of this central data consolidation.
Attackers may find centralized data aggregation appealing and manipulate the IoT system to their advantage, leading to catastrophic consequences3. Within the IoT environment, this raises confidentiality and security issues. A system that can use the current edge computing platform’s features and address some of these problems is needed to facilitate the scaled interconnected future.
IoT systems must interact and integrate with their surroundings safely and effectively4. These IoTs technologies provide enormous amounts of data that can be instantly processed and analyzed to aid decision-making process. Such processing should occur near the network’s edge to maximize timeliness and minimize bandwidth needs.
Edge computing can interpret data and make choices at the network’s edge. As a result, it is necessary to investigate the advantages and disadvantages of edge computing in IoT. Edge computing: an overview The massive influx of data from the IoT is straining cloud computing due to expensive bandwidth and high latency.
However, to meet the fundamental needs of the industry in areas such as real-time enterprise, artificial intelligence, security, and privacy, edge computing offers a service computing model that is near objects or data sources, enabling rapid response to various services5. In this section, we will outline the key features of edge computing. With edge computing, processing power is physically and conceptually near to the endpoints.
This means that everything from data production to data processing to data utilization occurs near the data source, ensuring a near-instantaneous response to requests from terminals. Edge servers can self-recover and operate independently in a network outage. The central cloud is responsible for executing flexible computational offloading and assigning tasks to appropriate edge servers.
Many diverse and adaptable edge devices are available to meet the increasing demands of the IoTs. In addition, servers located in edge computing surroundings may enhance cloud computing capabilities by providing these nearby diverse edge devices with enhanced storage, processing, and communication features. These enhanced features include increased data storage capacity, faster data processing speeds, and improved communication bandwidth, all of which contribute to the efficiency and performance of edge computing.
This shifts resources away from the cloud facilities and onto the edge, reducing the load on the cloud layer. Restricted Data Access is unnecessary to transport data to distant clouds since edge devices can collect and analyze data locally. Thus, security is improved to some level since most information, particularly private data, does not have to pass over the network.
With increasing processing power and storage space, the architecture progresses from the device layer to the core layer and back again. The device layer comprises many diverse IoT devices with limited resources and computing capability6. These devices include sensors, RFID tags, recording devices, automobiles, outside units, etc.
Their primary purpose is to gather, send out, and upload raw data, serving as the data collection and transmission hub of the IoT system. The edge layer supplies processing, storage, and network bandwidth to devices at the network’s periphery, acting as servers from a computational standpoint. The computer offloading methodologies of jobs and the coordination of associated resources are crucial to the edge layer because of the nature of edge server capacities and network architecture.
The core infrastructure typically indicates the cloud layer, whose topologies are comparable to cloud computing. The cloud layer must be invoked to finish the jobs the edge layer cannot handle. In addition, the cloud layer can adapt the edge layer’s deployment techniques in real time according to the constantly changing allocation of edge resources.
Blockchain: an overview Everyone has been talking about blockchain technology ever since Bitcoin was developed. A blockchain is a distributed ledger technology that can record financial transactions7. A hash label connects the blockchain’s most recent block to the one that came before it.
In particular, the following data can be stored in a blockchain block: 1. Information on the activities, including the time, date, and amount. 2.
Facts regarding the participants in those transactions. 3. A distinct hash code that distinguishes one block from another.
A new block is appended to the end of the blockchain for each transaction. Since the blockchain stores all transactions in a public ledger, which is a type of blockchain that is open to everyone, it is entirely transparent. Users’ identities and other sensitive information will be maintained securely on the public blockchain to protect their privacy8.
In addition to the hash of the data inside it, each block on the blockchain also includes the hash of the block that came before it. Therefore, a decentralized distributed ledger technology (DLT) is a common way to describe blockchain. It is challenging, if possible, for a hacker to alter a blockchain transaction without changing the hash of every block that follows it.
Blockchain is well-suited for use in several industries because of its inherent security, which includes finance, healthcare, government agencies, managing supply chains, and many more9. Blockchain transactions are confirmed and verified by a “consensus protocol,” as opposed to conventional systems that rely on a central authority to do the same. Using a consensus method, every node in the blockchain network may agree on the blockchain’s present state10.
A consensus algorithm must be implemented to ensure that all blockchain nodes agree on the present condition of the chain every time a new block is produced (via transactions). The consensus process is also performed when a new node is added to the blockchain. Therefore, consensus algorithms play a crucial role in establishing the trustworthiness of every node in the blockchain, ensuring the blockchain’s dependability and security.
Proof of Capacity, Proof of Stake, Proof of Burn, and Practical Byzantine Fault Tolerance are among today’s most widely utilized consensus algorithms. Smart contracts are implemented on a blockchain to guarantee that the transactions adhere to the specified conditions and limitations. Smart contracts, implemented with just a few lines of code, ensure that each transaction adheres to pre-agreed conditions.
This efficient automation relieves you from the manual task of confirming transactions, empowering you to make rapid and accurate decisions. The decentralization, immutability, and transparency of blockchain further enhance its appeal. (1) Decentralization: Before blockchain technology became popular, there used to be a single location where all the data was kept, and everyone could access it through this one location.
One point of failure, attack susceptibility, and other problems characterize centralized systems. Because all the nodes in a decentralized system have the data, it is possible to circumvent these problems with centralized systems. (2) Immutability: Data recorded on a blockchain cannot be altered because of consensus algorithms.
Blockchain is perfect for use in many industries because to this quality, including banking, supply chain management, regulation etc11. (3) Transparency: Each blockchain technology is perpetually open source. Anybody sees every transaction on the blockchain.
Since changes to the blockchain network require approval from most nodes, the technology or transactions remain safe despite their transparency. Complex cryptography techniques are used to conceal user information12. Implementing blockchain technology in decentralized systems, such as IoT, presents several significant challenges despite its numerous advantages.
Running consensus procedures, like PoW, on the blockchain causes considerable network latency and substantial energy consumption, a severe issue. For dispersed IoT networks where IoT devices have limited resources, this can be a dealbreaker for blockchain applications. The low data transfer rates of blockchain platforms is another issue.
Trust requirements for edge-based IoT systems Administration of trust for edge-based in the pursuit of a dependable system connecting IoT nodes to the edge network, IoT becomes an essential subject. The security challenges of edge computing-based IoT systems are shown in Fig. 1.
Precision It indicates how near a node’s computed trust value is to its fundamental or trust value when all information about its behavior is known. Accuracy in trust is crucial for the trust system of management 13 . Security If you want to be sure your edge-based IoT system is secure, you need to build trust.
When it comes to the infrastructure layer of edge servers, it does offer methods to guarantee security. Accessibility It means that the trust management system can guarantee that all network services will be fully available regardless of resources are attacked or unavailable for any other reason; this is especially frequent in edge networks. Dependability Trust management approaches rely on it as a crucial parameter.
The lifespan of the edge-based network guarantees that all functionalities perform correctly. Diversity Typical components of edge-based IoT include diverse subnets, nodes, edge nodes, and edge servers. For a trust management system to meet the diversity criteria, it must be able to accommodate objects with varying degrees of complexity, computational capacity, and use of energy.
Fig. 1 Edge computing based IoT systems and its security challenges. Full size image Lightweight Restricted devices and networks are a part of IoT systems that operate at the edge.
Because of this, edge-based IoT trust management frameworks need to be small and efficient enough to function effectively across a wide range of IoT nodes, networks, and servers, even when faced with limited resources 14 . Scalability and flexibility The IoT systems are constantly evolving, edge-based IoT must be very flexible and peers participating in trust-based transactions can change quickly. Additionally, regulations for assessing the credibility of edge servers and nodes are subject to frequent device changes, and the availability of their resources might vary widely15.
A new node can be introduced to the system, and a different application may need connectivity to these edge servers and nodes; nevertheless, an IoT device’s transmission and storage costs do not scale with the number of devices in the network. Motivations and contributions Blockchain and IIoT systems are inherently different, posing a significant challenge in their integration with edge computing. The limited resources of IoT devices and the need for a scalable security solution in the face of extensive IIoT networks further complicate industry system.
However, this study proposes a private blockchain-based architecture for the IIoT network that is lightweight, scalable, and specifically designed to tackle these difficulties. The potential of this proposed design is immense, offering a ray of hope in addressing the challenges of IIoT integration with blockchain. The following are some of the most important contributions of the proposed system.
1. Integrating blockchain with IoTs in a way that works for smart factories is a significant opportunity. This study proposes a private, decentralized, blockchain-based IIoT network that is not only lightweight but also highly extensible, ensuring its adaptability to the evolving needs of the industry.
2. In the proposed architecture, first step is implementing small nodes that use virtual machines to conduct asymmetric cryptography in real time. Secondly, the primary blockchain network implements a (PoAh) system.
This system, which is both scalable and compatible with the IoT, ensures that only authenticated devices can participate in the blockchain network, thereby enhancing its security and reliability. 3. Further, we examine the blockchain integrated IIoT paradigm’s security needs.
We specifically examine the way blockchain might help with important industry security services such as trust management, secure data sharing, device registration, and device authentication. The outline of the rest of the article is as follows: Sect. 2 covers the current state of blockchain technology as it pertains to IIoT systems.
Section 3 details the edge computing-enabled blockchain architecture. Section 4 details the proposed architecture and its operation model. Section 5 provides a comprehensive analysis of the system’s efficiency.
Lastly, Sect. 6 provides a concise summary16.
