Personal data stores (PDSs) are gaining attention as an alternative to the current systems used by tech giants to manage users' data. PDSs centrally manage user logs and data across services and enable data to be passed on to service providers in accordance with the user's own intentions. Using cloud servers to manage personal information is a natural choice from the perspectives of convenience and cost. Therefore, security is highly important in the PDS model. However, to the best of our knowledge, not enough research on encrypting PDS data has been conducted. This is because merely using conventional encryption schemes could compromise the functionality of PDSs. In this study, we developed a key-aggregate identity-based proxy re-encryption (KA-IB-PRE) scheme combining a key-aggregate cryptosystem technique with an identity-based proxy re-encryption scheme. Our approach is highly compatible with PDSs, and a system using KA-IB-PRE called EncPDS can construct a privacy-preserving model that meets their requirements. In particular, it offers advantages in privacy protection compared with existing methods, allowing for selective re-encryption of any data through key aggregation while keeping information about which data to re-encrypt hidden from the cloud.

Recently, various over-the-top (OTT) streaming services as well as traditional broadcasts distribute numerous content every day, allowing users to watch their favorite content at any time. While users can choose from a quantity of content, they often view the same content mainly because most OTT streaming services implement recommendation systems. However, it is often difficult for users to realize the same content they viewed and enjoy sharing their opinions or feelings because they do not know each other when and which content they viewed. For the purpose of encouraging such enjoyable experiences, we propose a system architecture that allows users to share the same content they viewed by using the user's viewing history data. Such viewing history data is currently collected and stored by hundreds of different services and companies. Therefore, our system architecture adopts a user-centric data control model that allows users to collect and store their data on their own online storages, and use it for their purposes. If users are asked to disclose all of the raw data of their viewing history to each other or to third party when sharing, most of them will feel anxiety because the data often contains sensitive personal information. Therefore, we introduce a method using private set intersection (PSI), a cryptographic technique that allows users to share the same elements in the users’ viewing history data without revealing anything to each other except the elements at the intersection. We also demonstrate the feasibility of the architecture through use cases.