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Identification and Differential PrivacySpecial Topics on Privacy and Public Auditability National Institute of Standards and Technology January 27, 2020, Simon L. Garfunkel Senior Computer Scientist

How to fill out de-identification and differential privacy

How to fill out de-identification and differential privacy

1. To fill out de-identification:
2. Identify the sensitive data that needs to be protected.
3. Determine the de-identification techniques to be used, such as removing direct identifiers or replacing them with pseudonyms.
4. Implement the chosen techniques to de-identify the data.
5. Test the effectiveness of the de-identification process to ensure the data is adequately protected.
6. Continuously monitor and update the de-identification process to adapt to changing threats and regulations.
7. To fill out differential privacy:
8. Define the privacy budget, which is a measure of how much noise will be added to the data to protect individual privacy.
9. Determine the utility functions that measure the usefulness of the data for intended analysis.
10. Apply noise or other privacy-enhancing mechanisms to the data in a way that preserves privacy while maintaining utility.
11. Quantify the privacy guarantees provided by the differential privacy mechanism.
12. Validate the effectiveness of the differential privacy mechanism through testing and evaluation.
13. Adjust the privacy parameters as needed to balance privacy and utility.

Who needs de-identification and differential privacy?

1. Anyone who deals with sensitive data and wants to protect individuals' privacy needs de-identification and differential privacy.
2. This includes organizations in industries like healthcare, finance, marketing, and research, as well as government agencies and individuals handling personal information.
3. De-identification and differential privacy are crucial for complying with data protection regulations, preventing identity theft, safeguarding confidentiality, and enabling data sharing while preserving privacy.

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What is de-identification and differential privacy?

De-identification is the process of removing or altering personal information from a dataset so that individuals cannot be readily identified. Differential privacy is a statistical technique that ensures the privacy of individual data by adding noise to aggregated data to prevent the identification of individuals within a dataset.

Who is required to file de-identification and differential privacy?

Organizations that collect, use, or disclose personal data, especially in research or data analysis contexts, are typically required to file de-identification and differential privacy to protect the privacy of individuals.

How to fill out de-identification and differential privacy?

To fill out de-identification and differential privacy, organizations should follow the guidelines set by relevant authorities, ensuring that they clearly document their data practices, techniques used for de-identification, and the methods employed for differential privacy.

What is the purpose of de-identification and differential privacy?

The purpose of de-identification and differential privacy is to protect individual privacy while allowing organizations to utilize data for analysis and research, ensuring that personal identifiers are removed or obscured to prevent re-identification.

What information must be reported on de-identification and differential privacy?

Organizations must report on the methods used for de-identification, the types of data that were transformed, the potential risks of re-identification, and the differential privacy guarantees provided.