Copyright and privacy protection for digital music with the implementation of distributed ledger technology and deep learning

The presence of music in our daily lives is ubiquitous. Digital musical works are created utilizing Distributed Ledger Technology and Deep learning, with their creation serving as a case study for the exploration of computerized computation, analysis of copyright, and online music administration. The problems of copyright validity and code safety are not yet fully handled in digital music. This study proposes the Digital Music Copyright and Protection (DMCP) model to analyze digital music's legal protection and management. Two-stage deep learning and distributed ledger technology are used to implement DMCP in digital music production. With the automated structure and deployment of neural network-based approaches geared toward deep learning, the Deep Neural Network (DNN) is launched. Blockchain technology improvement examines the problems with traditional copyright rights and digital music administration. Digital music copyright and protection now incorporate blockchain, which fully accounts for ownership, usage rights, and security. The DMCP concept provides the highest level of security available by combining automated computers, digital music, and distributed ledger technology. The experimental outcomes of the proposed methodology have improved prediction accuracy, music quality, music sustain ability, and copyright protection.