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Using Blockchain in Resolving the Challenges Faced by IIoT
Published in Sudan Jha, Usman Tariq, Gyanendra Prasad Joshi, Vijender Kumar Solanki, Industrial Internet of Things, 2022
Practical Byzantine fault tolerance is an algorithm that makes it possible for one-third of the nodes not to agree with the rest, but still to send through a block. In what is called a round, blocks are generated where a primary node is selected based on certain rules collection. Then this primary node is in charge of the block formation. Three stages have to be completed to create a block where two-thirds of the nodes have to vote it through each time. Since this solution is based on a specific number of nodes, all nodes in the network must be identified in order for it to function [18]. Ripple uses an approach inside the larger blockchain network where collectively trusted subnetworks are built. The nodes here can be either a client or a server. Servers function like a subnet’s main node and manage the validation of new blocks when passing funds only to clients. Servers have a specific list of nodes that are used to decide which nodes a validation request should be sent to. The server adds it to the chain if 80% of the nodes in the list agree that the transaction should be added. Both servers in the wider network share the blockchain [18]. Different consensus mechanism is summarized in Table 11.1
Blockchain
Published in Naveen Chilamkurti, T. Poongodi, Balamurugan Balusamy, Blockchain, Internet of Things, and Artificial Intelligence, 2021
S. Suganthi, T. Lucia Agnes Beena, D. Sumathi, T. Poongodi
Byzantine fault tolerance is the ability of a distributed network to function and reach a consensus, even when the network nodes fail to respond, or they respond incorrectly. The term is derived from the Benzantine Generals Problem. It can handle up to one third of malicious user nodes in a group of nodes. The node for publishing is selected in a round. Based on certain rules a primary node is selected in each round, which carries out the transactions and all other nodes are secondary nodes. The process has three phases: pre-prepared, prepared, and commit. If a node gains two thirds of the votes from all other nodes in each phase, it can pass through the successive phases.
Security and Privacy in IoT
Published in Brojo Kishore Mishra, Sanjay Kumar Kuanar, Sheng-Lung Peng, Daniel D. Dasig, Handbook of IoT and Blockchain, 2020
Neelamani Samal, Debasis Gountia
In relation to distributed systems, Byzantine Fault Tolerance is the capability of a distributed network to execute as required and correctly reach a consensus despite malicious nodes. It is derived from the Byzantine General Problem, where the general sends an attack message to one group of lieutenants whereas he sends a retreat message to another group of lieutenants. Hence it becomes difficult for the system to find out what action to take. Byzantine fault-tolerant systems are typically built using replication. For this, the state machine approach is used which helps to implement fault-tolerant services. The variant of BFT that has been designed for synchronous distributed systems is called the “Lamport–Shostak–Pease” algorithm. This ensures consensus in presence of a number of faulty nodes, provided we have (2f + 1) number of lieutenants apart from the commander. But our real systems behave in an asynchronous way as there is no guarantee that a message will be received within a certain time interval. For this reason, a variant of BFT known as Practical Byzantine Fault Tolerance (PBFT), has been developed for real-life asynchronous systems. As in the case of a pure asynchronous system, achieving consensus is impossible even in the presence of a single faulty node. So to ensure liveness property, instead of pure asynchronous system, a weak asynchronous system has been considered. Coming to the algorithm, the byzantine model consists of three types of nodes: the clients, a commander and the lieutenants. The entire algorithm runs in three phases: pre-prepare, prepare and commit phase. In the pre-prepare phase the commander assigns a sequence number to the request submitted by a client and multicasts it to the network. Among other data, the request message also contains the digital signature and message digest for verification. The lieutenants of the network confirm the block by verifying the digital signature and message digest. Once the validating lieutenants accept the pre-prepare message, they enter the prepare phase by multicasting the message to the rest of the network. Once again both the commander and lieutenants verify the prepare messages before accepting them. The messages commit, when (2f) prepare message from different backups match with the corresponding pre-prepare messages. Hence, the total (2f + 1) votes one from primary from the non-faulty replica help the system to reach to a consensus. With the evolution of ICT, the blockchain technology has attracted interest from various directions. The consensus algorithm is the main technology of blockchain. In the case of permissionless systems, it is easy to achieve robust consensus among large number of untrusted nodes using complex computations though transaction, finally remains non-deterministic. On the contrary, permissioned blockchain provides high throughput in less time while sacrificing a degree of decentralization.
Secure and Privacy in Healthcare Data Using Quaternion-based Neural Network Cryptography with the Blockchain Mechanism
Published in IETE Journal of Research, 2023
Based on blockchain technology, privacy preservation of large-scale health care data is performed. Fine-grained access control is undertaken by encrypted medical data. For key management, by leveraging user transactions the authorized doctors are effectively revoked. The communication overhead has been reduced compared with traditional methods. The major drawback indicated that if the size of transactions is minimized then blockchain storage has been reduced [20]. Another study also focused on user privacy and which the blockchain method has been used. For managing the size of the blockchain, the non-sensitive information is transferred to the other primary system, whereas the sensitive information is preserved in a distributed blockchain. Within the individual user device, the computational capacity and local database storage are restricted by these proposed synchronizing operations using the DEPLEST algorithm (Distributed partial ledger storage technique). This protocol shows better byzantine fault tolerance. Compared with traditional proof of stake and proof of work techniques the DEPLEST algorithm shows better results.
‘Un’-blocking the industry 4.0 value chain with cyber-physical social thinking
Published in Enterprise Information Systems, 2023
Subodh Mendhurwar, Rajhans Mishra
A block comprises (a) block header and (b) block body (transaction counter with transactions) (Zheng et al. 2018). The block header typically consisting of (i) block version (an indicator of applicable block validation rules), (ii) parent block hash (previous block pointer), (iii) Merkle tree root hash (of all earlier transactions), current timestamp, current hashing target (typically decided by the network) and (iv) nonce (increments for every hash computation till solution arrived or target changed). Existing blockchains typically use four major consensus mechanisms: (i) PoW (Proof of Work), e.g., Bitcoin and Ethereum, (ii) PoS (Proof of Stake), e.g., PeerCoin, ShadowCash, (iii) PBFT (Practical Byzantine Fault Tolerance), and (iv) DPoS (Delegated Proof of Stake);besides others such as PoB (Proof of Bandwidth), PoET (Proof of Elapsed Time), PoA (Proof of Authority), e.g., Ethereum (Li et al. 2020), Ripple, Tendermint, PeerConsensus, GHOST, etc. (Zheng et al. 2018), or specialised mechanisms (‘Proof of X’ – Yu et al. 2020) for niche requirements (e.g., lightweight blockchain-based, distributed trust architectures for IoT – e.g., Dorri, Kanhere, and Jurdak 2017; Dorri et al. 2019).
Blockchain-based ubiquitous manufacturing: a secure and reliable cyber-physical system
Published in International Journal of Production Research, 2020
Ali Vatankhah Barenji, Zhi Li, W. M. Wang, George Q. Huang, David A. Guerra-Zubiaga
As mentioned previously, the main aim of this research was to integrate BC into the CM and UM and highlight peer-to-peer communication in order to omit the third party. Several contributions are of significance. A new architecture for blockchain cloud-based ubiquitous manufacturing has been developed, to solve scalability and trust problems in SMEs. Advanced ICT technologies, including agent-based communications and CPS, are used in the machine-level environment to create real-time communication between physical and software platform levels. The proposed platform is able to provide a peer-to-peer network with useful information passing between the service user and service provider.In order to improve the blockchain network and adapt this technology to industrial applications, Byzantine fault tolerance is used to develop a new algorithm for supporting the consensus mechanism in the blockchain network. The proposed pBFT algorithm is compared with the PoW algorithm.A blockchain platform is developed for 3D printing and an empirical case study is explained. We considered three different experiments. The first experiment focused on evaluation of the proposed network, and pBFT was compared with PoW. The second experiment focused on the scalability of the network, considering cloud environment evaluation. Finally, we focused on security evaluation of the proposed platform with standard experiment.