TY - GEN
T1 - A Review of Recent Trends in Blockchain Consensus Algorithms
T2 - 28th Asia-Pacific Conference on Communications, APCC 2023
AU - Windiatmaja, Jauzak Hussaini
AU - Salman, Muhammad
AU - Sari, Riri Fitri
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Blockchain has emerged as an important technology, offering safe, decentralized, and transparent platforms for recording and validating transactions. Blockchain technology consist of several main components, i.e., consensus algorithm. The consensus algorithm guarantees that all participating nodes in a blockchain network agree over the data control. Traditional consensus methods, such as Proof of Work (PoW) and Proof of Stake (PoS), present issues in terms of energy consumption and attack vulnerability. To overcome these constraints, there has been a rising interest in incorporating Artificial Intelligence (AI) techniques, especially deep learning, into blockchain consensus algorithms. We highlight blockchain fundamentals in this article, while also stressing the importance of the consensus algorithm. Furthermore, we address the most recent advancements in blockchain consensus methods in both performance-based and reputation-based paradigm, emphasizing the use of AI inside these decentralized systems. The use of AI, especially deep learning, in consensus algorithms has the potential to overcome the limitations of previous techniques. Blockchain networks may improve its performance by employing AI capabilities. However, incorporating AI into blockchain consensus algorithms is having its own challenges. Therefore, we also highlight several issues related with AI-based techniques in blockchain consensus algorithms, such as dealing with the quality and variety of data utilized by consensus algorithms and maintaining the openness of the AI models. In addition to those challenges, we propose a future direction for the AI-based approach in blockchain, which includes merging the mechanisms of performance-based and reputation-based consensus algorithms to incorporate the merits of both methods.
AB - Blockchain has emerged as an important technology, offering safe, decentralized, and transparent platforms for recording and validating transactions. Blockchain technology consist of several main components, i.e., consensus algorithm. The consensus algorithm guarantees that all participating nodes in a blockchain network agree over the data control. Traditional consensus methods, such as Proof of Work (PoW) and Proof of Stake (PoS), present issues in terms of energy consumption and attack vulnerability. To overcome these constraints, there has been a rising interest in incorporating Artificial Intelligence (AI) techniques, especially deep learning, into blockchain consensus algorithms. We highlight blockchain fundamentals in this article, while also stressing the importance of the consensus algorithm. Furthermore, we address the most recent advancements in blockchain consensus methods in both performance-based and reputation-based paradigm, emphasizing the use of AI inside these decentralized systems. The use of AI, especially deep learning, in consensus algorithms has the potential to overcome the limitations of previous techniques. Blockchain networks may improve its performance by employing AI capabilities. However, incorporating AI into blockchain consensus algorithms is having its own challenges. Therefore, we also highlight several issues related with AI-based techniques in blockchain consensus algorithms, such as dealing with the quality and variety of data utilized by consensus algorithms and maintaining the openness of the AI models. In addition to those challenges, we propose a future direction for the AI-based approach in blockchain, which includes merging the mechanisms of performance-based and reputation-based consensus algorithms to incorporate the merits of both methods.
KW - Artificial Intelligence
KW - Blockchain
KW - Consensus Algorithm
KW - Deep Learning.
UR - http://www.scopus.com/inward/record.url?scp=85188452194&partnerID=8YFLogxK
U2 - 10.1109/APCC60132.2023.10460688
DO - 10.1109/APCC60132.2023.10460688
M3 - Conference contribution
AN - SCOPUS:85188452194
T3 - Proceedings - 2023 28th Asia Pacific Conference on Communications, APCC 2023
SP - 335
EP - 341
BT - Proceedings - 2023 28th Asia Pacific Conference on Communications, APCC 2023
A2 - Le, Khoa N
A2 - Bao, Vo Nguyen Quoc
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 19 November 2023 through 22 November 2023
ER -