## 4 Applications Utilizing Music Usage Data Based on AI
### Pseudonymization of Music Usage Information  
Music usage information can be used for various purposes other than settlement or distribution. The usage information data in various fields have considerable inherent asset value, as in the case of MyData services in the finance field. However, in the music industry, the utilization of music usage information is limited due to the Personal Information Protection Act. Music rights holders give authority over their music rights to associations, and they permit the use of music-by-music distributors. Therefore, the personal information for the music is fragmented, and no one can carry out applications using the music usage information. However, in the proposed system, an agreement, such as usage consent, is previously constructed by registering the music in the first step, so that it will be immune from the legal issues. For the effective protection of personal information, it is more convenient that the pseudonymization of the music usage data be performed. This chapter discusses the ways in which public services or OSPs could utilize music usage data through pseudonymization before AI-based applications.  
Music usage data contain personal information that is necessary to de-identifify. The de-identification of personal information refers to the deletion or modification of part or all of this personal information so that a specific individual cannot be identified. The related guidelines in Korea provide five methods: pseudonymization, aggregation, data reduction, data suppression, and data masking. These five methods can be divided into anonymization and pseudonymization, depending on the deletion of personal identification. Anonymized information can be freely utilized because of the impossibility of re-identification; however, it lacks utility. On the other hand, pseudonymization data do not allow one to recognize individuals without additional information. Therefore, it can be used for purposes such as statistics, research, and the preservation of records of public interest [11; 12].  
The pseudonymization of music usage information could be undertaken by the OSP that produces the data; however, the popular method is to choose an independent organization that can deal with pseudonymization through the de-identification of data. Figure 5 shows a process diagram for managing the unique key of an independent organization. The transmitted music usage data are pseudonymized using a JAVA-based, high-speed, one-way pseudonymization module. Here, the pseudonymization algorithm needs two key functions. First, since the amount of day-based music usage data is large, it is easy to process pseudonymization only when the computing time of the algorithm is  
Figure 4: An example of a settlement and distribution system applying all three modules.  
extremely short. Second, it is necessary that the same identifier be used (for continuity) for the previous and current data. This is because the utility of music usage data can be increased only when there is continuity of the same music. Figure 6 shows an example of a polymorphic pseudonymization algorithm module that makes the de-identified data stable. The advantages of the polymorphic pseudonymization process are its competitiveness, wide-spread data usage, and independence of the data. Therefore, it could be helpful for effective human resource and service improvement.