A Decentralized Music Copyright Operation Management System Based On Blockchain Technology

Li, Yanghuan; Jinhui, Wei; Yuan, Junbin; Xu, Qingzhen; He, Chengying

doi:10.1016/j.procs.2021.04.084

Cited by 19 publications

(5 citation statements)

References 6 publications

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“…However, contractual challenges can complicate settlement operations, potentially resulting in a “black box” of proceeds. The royalty percentage distributed in this manner depends on music consumption, which currently cannot be directly linked to the copyright owner (Li et al., 2021). Examples include music played at events, in stores, or from YouTube clips.…”

Section: Systematic Literature Review and Findings Of Blockchain Appl...mentioning

confidence: 99%

Blockchain in the age of industrial revolution: A systematic literature review using bibliometric analysis

Gupta,

Meena,

Dhir

2023

Glob Bus Org Exc

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The emergence of blockchain technology has spurred research and industrial advances, presenting potential benefits and practical solutions for various industries and their communities. Blockchain technology enables the efficient distribution, sharing, and secure storage of transactional data, leading to increased transparency and productivity in supply chains. While blockchain is seen as a disruptive technology, it is essential to explore its applicability to various industries. To this end, this study conducts a bibliometric analysis of the extant blockchain literature to better understand its potential applications. The study presents a systematic literature review that highlights the practical application of blockchain technology transfer in various industries, such as pharmaceuticals, banking and financial services, and media and entertainment.

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Section: Systematic Literature Review and Findings Of Blockchain Appl...mentioning

confidence: 99%

Blockchain in the age of industrial revolution: A systematic literature review using bibliometric analysis

Gupta,

Meena,

Dhir

2023

Glob Bus Org Exc

View full text Add to dashboard Cite

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“…Li et al [ 16 ] introduced a blockchain-based decentralized music copyright operation management system that disconnects the link between activities and property. They created a distributed licensing management system utilizing the blockchain's shared ledger system and smart contracts as the Ethereum platform's main structure [ 17 ].…”

Section: Related Literaturementioning

confidence: 99%

Combination of Blockchain and AI for Music Intellectual Property Protection

2022

Computational Intelligence and Neuroscience

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In the last two years, due to the pandemic and restrictive measures, the dependence of music creators and artists on the Internet, where they could promote their work, organize live streaming concerts, and talk to the public, has increased and expanded even more and seeks higher revenue from digital music platforms. An important issue that arises from the above statement is protecting the authors’ copyright regarding the uses and sharing in the digital services of their works with protected content. Although circulated in digital information, the protected content is not information but a product of ethical and commercial value. While it has an intangible owner and it owes its existence to the creative idea of its creator, it is not an idea. The imposition of legal and commercial conditions on its movement cannot be associated with any restrictions on the free movement of information, as it is not related to them. In general, the unauthorized exchange of digital music files via peer-to-peer violates copyright law. The exchange of files is unauthorized, as it does not have the relevant permission from the creators and beneficiaries and is therefore illegal. With this in mind, this paper proposes a highly effective way of protecting the copyright of music technology, which is based on the widespread use of artificial intelligence, blockchain, and cryptography technologies. Specifically, an advanced blockchain model based on Hyperledger Fabric is introduced, which, however, uses Quantum Homomorphic Encryption and Quantum Zero-Knowledge Arguments. Music files are implemented as Nonfungible Tokens (NFTs), which activate smart contracts. Finally, an advanced collaborative filtering algorithm provides recommendations for effectiveness in securing the copyrights of music industry creators. A specialized scenario was built to model the proposed system to verify the degree of protection on music intellectual property in developing a security simulation with an innovative consensus-based zero knowledge and the quantum fully homomorphic encryption technique. Experiment results show that this technique can aid in implementing a technologically aware system capable of providing a powerful answer to a current real-world problem.

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“…While cryptocurrencies are only a small part of the applications of blockchain technology, its immutable nature gives it a much wider scope for development. In recent years, more and more researchers have taken advantage of its properties to use it in areas such as drug storage and transportation [19], financial transaction ledgers [20], and identity and copyright authentication [21]. Governments are also investigating it for its immense practical value [22][23][24].…”

Section: Background and Related Workmentioning

confidence: 99%

Phishing Scam Detection on Ethereum via Mining Trading Information

Chen¹,

Fu²

2022

Journal of Cyber Security

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As a typical representative of web 2.0, Ethereum has significantly boosted the development of blockchain finance. However, due to the anonymity and financial attributes of Ethereum, the number of phishing scams is increasing rapidly and causing massive losses, which poses a serious threat to blockchain financial security. Phishing scam address identification enables to detect phishing scam addresses and alerts users to reduce losses. However, there are three primary challenges in phishing scam address recognition task: 1) the lack of publicly available large datasets of phishing scam address transactions; 2) the use of multi-order transaction information requires a large number of queries and computations; and 3) the extraction of phishing scam address features relies on machine learning methods excessively, which leads to the loss of practical meaning and is harmful to the research of phishing scam addresses. This paper proposes a systematic phishing scam address recognition scheme, to simultaneously overcome the three challenges in phishing scam address recognition. In this paper, a systematic phishing scam address recognition scheme is proposed to addresses these issues. Specifically, due to the insufficient number of address tagged in the existing publicly available Ethereum phishing scam address transaction dataset, we first construct a transaction dataset involving over 10000 tagged addresses. To the best of our knowledge, this is the largest dataset of tagged addresses for Ethereum phishing scam detection. Then, we design a new heuristic rule to implement feature extraction of address nodes by analysing the traditional financial involved accounts combined with information specific to Ethernet transactions. After that, a novel adaptive feature importance filtering method is designed to adaptively adjust the filtering threshold based on the final classification results, which reduce the feature dimensionality while ensuring a certain detection performance. Finally, random forest is used to classify whether the addresses is a phishing scam address or not. Extensive experiments on real Ethereum datasets show that our approach (98.89% Precision, 98.35% Recall, 98.62% F1) achieves state-of-the-art performance.

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A Decentralized Music Copyright Operation Management System Based On Blockchain Technology

Cited by 19 publications

References 6 publications

Blockchain in the age of industrial revolution: A systematic literature review using bibliometric analysis

Blockchain in the age of industrial revolution: A systematic literature review using bibliometric analysis

Combination of Blockchain and AI for Music Intellectual Property Protection

Phishing Scam Detection on Ethereum via Mining Trading Information

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