Back to Search Start Over

MBE: A Music Copyright Depository Framework Incorporating Blockchain and Edge Computing.

Authors :
Jianmao Xiao
Ridong Huang
Jiangyu Wang
Zhean Zhong
Chenyu Liu
Yuanlong Cao
Chuying Ouyang
Source :
Computer Systems Science & Engineering; 2023, Vol. 47 Issue 3, p2815-2834, 20p
Publication Year :
2023

Abstract

Audio copyright is a crucial issue in the music industry, as it protects the rights and interests of creators and distributors. This paper studies the current situation of digital music copyright certification and proposes a music copyright certification framework based on "blockchain + edge computing mode," abbreviated as MBE, by integrating edge computing into the Hyperledger Fabric system. MBE framework compresses and splits the audio into small chunks, performs Fast Fourier Transform (FFT) to extract the peak points of each frequency and combines them to obtain unique audio fingerprint information. After being confirmed by various nodes on the Fabric alliance chain, audio fingerprint information and copyright owner information are recorded on the chain and broadcast to all participants. Blockchain technology's characteristics of being tamper-proof and traceable not only reform the trust mechanism of copyright protection but also endow edge computing with the ability to resist tampering and single-point attack, greatly enhancing the robustness of the music copyright certification system. Meanwhile, edge computing mode improves Fabric blockchain's processing speed and transaction throughput. Experimental results show that MBE's performance is better than traditional systems regarding efficiency, storage demand and security. Compared to the traditional Fabric system without edge computingmode,MBE exhibits a 53% higher deposition efficiency and a 48% lower storage space requirement. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02676192
Volume :
47
Issue :
3
Database :
Supplemental Index
Journal :
Computer Systems Science & Engineering
Publication Type :
Academic Journal
Accession number :
173709080
Full Text :
https://doi.org/10.32604/csse.2023.039716