|
|
| Privacy Technique |
Description |
| Data Minimization |
Data minimization is a privacy approach that involves collecting and processing only the data that is necessary for a specific purpose. By limiting the amount of personal data collected, stored, and used, organizations can reduce the risk of data breaches and unauthorized access. |
| PI Redaction |
Personally Identifiable Information (PII) redaction is the process of removing or masking sensitive information from documents or datasets to protect individuals' privacy. This technique helps prevent the exposure of personal data in case of unauthorized access or data leaks. |
| Data Aggregation |
Data aggregation involves combining and summarizing data from multiple sources to provide insights without revealing individual identities or sensitive details. This technique helps protect privacy by anonymizing data while still allowing for analysis and decision-making based on aggregated information. |
| Anonymization |
Anonymization is the process of removing personally identifiable information from datasets to ensure that individuals cannot be identified. This technique helps protect privacy by de-identifying data, making it more difficult to trace back to specific individuals. |
| Encryption |
Encryption is a method of encoding data to make it unreadable without the appropriate decryption key. By encrypting sensitive information, organizations can protect data both in transit and at rest, enhancing privacy and security. |
| Access Controls |
Access controls involve implementing mechanisms to restrict and manage access to data based on user roles and permissions. By controlling who can view, edit, or delete data, organizations can prevent unauthorized access and protect privacy. |
|