## 3 Related Work
### Methods of Protection and Regulatory Aspects
In this aspect, the most challenging part is related to the user's location and location of the user's data [35]. There are numerous examples of related works on storing data on various Internet platforms. The field of data storage is constantly evolving, as new technologies and methodologies emerge to address the challenges of managing and storing large-scale data in distributed environments [36]. In this regard, authors in [36] proposed a platform called PRIPRO (\"Privacy Profiles\"), designed to address user profiling and data storage concerns in smart environments while emphasizing privacy. This concept is crucial as smart environments often collect and utilize user data for various purposes, including automation, personalization, and analytics. This platform also includes mechanisms for securely storing user profiles and associated data. This includes encryption, access control, and data retention policies. The platform presented in this paper assists in defining the set of rules for the smart environment and updating the user's profile. Based on that, authors implemented a solution that is composed of a client application to run on the user's smartphone and a web server in order to manage the evolution of the user's profile and permissions. Authors in [37] presented the middleware Ubiquitous Privacy (UbiPri) for the control and management of data privacy based on a generic model. This model includes several modules, such as Data Base, Controller module, Data module, Privacy Control Management User (PRICMU), Privacy Communication (PRICOM), Privacy Devices (PRIDEV), Privacy Profile (PRIPRO), Privacy Adaptation (PRIADA), Privacy Environment (PRIENV), Privacy Criteria (PRICRI), Privacy History (PRIHIS), and Privacy Security (PRISEC). The PRIHIS module stores and handles information related to the user's history, environment, devices, and other variables that can be added later to obtain contextual information. It is important to mention that all modules work independently, with characteristics that vary according to the rules previously established in the environment. Therefore, for a module to be able to operate correctly, access is allowed to the data contained in the database. When it comes to Internet services, we know that they collect our personal data on a daily basis. At the beginning, Internet services have collected only a few types of personal data, such as names, ages, birthdays, etc., but with the rapid spread of social networks and personalized services, more and more personal data have been collected. Furthermore, according to authors in [38], IoT devices are increasingly being adopted by consumers, making it possible for companies to capture personal data, including sensitive data, with much less effort and at very low cost. Recent systems architectures aim to collect, store, and process personal data in the cloud with very limited control available to end-users. Therefore, a platform called Personal Data Stores (PDS) has been proposed as an alternative architecture where personal data will be stored, giving the users complete control over their data. On the other side, data sovereignty is another concept to the PDS model, which is defined as the capability of users to have full control as well as to determine their restrictions about the usage of their data, such as access control, authorization, usage duration, etc., before sharing with third parties.