From the course: CompTIA SecAI+ (CY0-001) Cert Prep

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Data minimization

Data minimization

From the course: CompTIA SecAI+ (CY0-001) Cert Prep

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Data minimization

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Data minimization is the principle of collecting, using, and keeping only the minimum amount of data needed for a specific purpose. It is one of the most effective ways to reduce security risks and stay compliant with privacy laws. If an organization never collects unnecessary data, that data cannot be stolen, leaked, or misused later. The principle of data minimization is especially important when collecting training data. During this stage, teams should carefully decide how much detail is truly necessary for the model's purpose. For example, a language model built to check grammar does not need to include full names in its training sentences. It only requires a text. By removing unnecessary identifiers, organizations can protect privacy and reduce the risk of exposure if the data set is compromised. Data minimization also applies to the information included in prompts. When an AI assistant receives a question, it might need additional context, such as user history or location, to…

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