Primary Node Selection Algorithm of PBFT Based on Anomaly Detection and Reputation Model

Gu, Ruowen; Chen, Bin; Huang, Dongyan

doi:10.1007/978-981-16-6554-7_178

Cited by 9 publications

(4 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To evaluate the reliability, dynamics, and latency of the proposed mechanism, we compared RPBFT with PoW [3], DPoS [5], PBFT [6], and the other related PBFT-type consensus algorithms [9][10][11][12].…”

Section: Experiments and Results Analysismentioning

confidence: 99%

“…First, the covariance matrix C= 1 m XX T is computed by (4). Then we solve for the corresponding eigenvalues and eigenvectors with (5). The eigenvectors are unitized as Pi by ( 6), and the diagonalized matrix P is obtained by arranging the eigenvalues in descending order.…”

Section: X=x-u=mentioning

confidence: 99%

“…With the boost of Blockchain technology [1], a frenzy of research and applications emerge based on the features of decentralization, unforgeability, untempering, anonymity, etc. As one of the core elements, consensus algorithm plays a pivotal role in blockchain distributed systems, e.g., PoW [2], PoS [3], DPoS [4], PBFT [5], Paxos [6], Raft [7], aiming to solve the consistency problem of nodes in different regions, especially in the typical Byzantine general problem [8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Sun

Wang

et al. 2022

Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022)

View full text Add to dashboard Cite

With the development and application of Blockchain technology, some consensus algorithms emerged. Practical Byzantine Fault Tolerance (PBFT), as a type of classic consensus algorithm, has been widely applied in Consortium Blockchain. However, it still has some issues need to be resolved via optimization, such as low node reliability, poor scalability, insufficient dynamics, and frequent view change. To address those problems, this paper proposes a Reputation evaluationbased fault tolerance consensus algorithm, named RPBFT. We introduce a reputation evaluation model based on the service performance and enthusiasm of nodes to participate in consensus. A reward-punishment mechanism is proposed to make nodes with high reliability more likely to participate in block production, which improves the security and reliability of the blockchain. Finally, a two-phase consensus process is presented to achieve a more efficient consensus. The experimental results show that, compared with relevant consensus algorithms, RPBFT is superior in reducing consensus delay and improving communication efficiency.

show abstract

Section: Experiments and Results Analysismentioning

confidence: 99%

Section: X=x-u=mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Sun

Wang

et al. 2022

Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022)

View full text Add to dashboard Cite

show abstract

“…Gu [23] et al utilized machine learning for node anomaly detection and used the result of anomaly detection as a factor for evaluating the reputation value. Since the master node can generate blocks, random numbers are added to the reputation model to prevent centralization and ensure the fairness of the master node election.…”

Section: Et Al Introduced Anmentioning

confidence: 99%

Grouped Multilayer Practical Byzantine Fault Tolerance Algorithm: A Practical Byzantine Fault Tolerance Consensus Algorithm Optimized for Digital Asset Trading Scenarios

Liu,

Feng,

Huang

et al. 2023

Sensors

View full text Add to dashboard Cite

Based on the practical Byzantine fault tolerance algorithm (PBFT), a grouped multilayer PBFT consensus algorithm (GM-PBFT) is proposed to be applied to digital asset transactions in view of the problems with excessive communication complexity and low consensus efficiency found in the current consensus mechanism for digital asset transactions. Firstly, the transaction nodes are grouped by type, and each group can handle different types of consensus requests at the same time, which improves the consensus efficiency as well as the accuracy of digital asset transactions. Second, the group develops techniques like validation, auditing, and re-election to enhance Byzantine fault tolerance by thwarting malicious node attacks. This supervisory mechanism is implemented through the Raft consensus algorithm. Finally, the consensus is stratified for the nodes in the group, and the consensus nodes in the upper layer recursively send consensus requests to the lower layer until the consensus request reaches the end layer to ensure the consistency of the block ledger in the group. Based on the results of the experiment, the approach may significantly outperform the PBFT consensus algorithm when it comes to accuracy, efficiency, and preserving the security and reliability of transactions in large-scale network node digital transaction situations.

show abstract

A Leadership Transfer Algorithm for the Raft

Huang

2022

Communications in Computer and Information Science

View full text Add to dashboard Cite

Primary Node Selection Algorithm of PBFT Based on Anomaly Detection and Reputation Model

Cited by 9 publications

References 7 publications

Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Grouped Multilayer Practical Byzantine Fault Tolerance Algorithm: A Practical Byzantine Fault Tolerance Consensus Algorithm Optimized for Digital Asset Trading Scenarios

A Leadership Transfer Algorithm for the Raft

Contact Info

Product

Resources

About