@inproceedings{189b24d4de404c8ca6f1a6798c62fa50,
title = "Fast Adaptive Blockchain{\textquoteright}s Consensus Algorithm via Wlan Mesh Network",
abstract = "This paper presents a decentralised and fast adaptive block chain{\textquoteright}s consensus algorithm with maximum voter privacy using wlan mesh network. The algorithm is suitable for consortium blockchain and private blockchain, and is written as a smart contract for Hyperledger Fabric. Unlike previously proposed blockchain{\textquoteright}s consensus protocols, this is the first implementation that does not rely on any trusted authority to compute the tally or to protect the voter{\textquoteright}s privacy. Instead, the algorithm is a fast adaptive protocol, and each voter is in control of the privacy of their own vote such that it can only be breached by a full collusion involving all other voters. The execution of the protocol is enforced using the consensus mechanism that also secures the Fabric blockchain. This paper tests the implementation on Fabric{\textquoteright}s official test network to demonstrate its feasibility. Also, this paper provides a computational breakdown of its execution cost.",
keywords = "Blockchain, Consensus algorithm, Hyperledger Fabric, Wlan mesh",
author = "Xin Jiang and Mingzhe Liu and Feixiang Zhao and Qin Zhou and Ruili Wang",
note = "Publisher Copyright: © 2020, Springer Nature Switzerland AG.; 2nd International Conference on Security with Intelligent Computing and Big-data Services, SICBS 2018 ; Conference date: 14-12-2018 Through 16-12-2018",
year = "2020",
doi = "10.1007/978-3-030-16946-6_1",
language = "English",
isbn = "9783030169459",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "3--16",
editor = "Jain, {Lakhmi C.} and Jain, {Lakhmi C.} and Ching-Nung Yang and Sheng-Lung Peng and Jain, {Lakhmi C.} and Jain, {Lakhmi C.}",
booktitle = "Security with Intelligent Computing and Big-data Services - Proceedings of the 2nd International Conference on Security with Intelligent Computing and Big Data Services SICBS-2018",
address = "Germany",
}