Databases are often used to store data necessary for training AI algorithms. This data can come from various sources, such as surveys, social networks, IoT sensors, etc. The data is collected, cleaned, and organized into databases for use in the Machine Learning process. AI algorithms analyze this data and learn to recognize patterns that allow them to make intelligent decisions. The results of the analysis are also stored in the database for later use.
However, when these databases are stored on unprotected servers, they can be vulnerable to hacker attacks. Hackers can steal data stored in the database, compromising the confidentiality of user and business data.
It is therefore crucial to protect databases used in AI and Machine Learning.
User privacy protection The collected data may contain sensitive information about users, such as their name, address, social security number, and other personal information. If this data is compromised, it can lead to adverse consequences for users, such as identity theft.
Intellectual Property Protection Databases benefit from dual protection as they are protected by copyright, provided the structure is original, and regarding the content, provided you can prove that you initiated it and that efforts and investments have been made.
With regular deposits, Ziplo allows you to create the necessary evidence to demonstrate the originality of your work, both in the structure of the database and its content.
Both in terms of protecting your intellectual property and in terms of its enhancement, these deposits are essential to establish traceability of your work.
Moreover, if you need to exchange datasets, Ziplo also allows you to share your data via a sovereign service.
