Using SmartNoise Python Library to Increase Privacy for Your Data Set

Correct Answer: D.

Option A is incorrect because the epsilon value must be a non-negative number.

Option B is incorrect because the higher the value of the epsilon parameter, the lower the level of privacy (i.e.

the level of noise used to distort the raw data)

Epsilon should be set below 1 in order to achieve a proper level of differential privacy.

Option C is incorrect because delta is the probability that the data is not totally private.

The higher the epsilon, the higher its value is.

In general, the epsilon value is used.

Since it is a measure of probability, it must be between 0 and 1.

Option D is CORRECT because in order to ensure differential privacy, the epsilon value must be set between 0 and 1

This ensures a sufficiently high level of noise to mask the raw data while leaving the statistical characteristics of the data set undistorted.

Diagram:

The above diagram shows the process of adding noise (Step 6) to the raw data in order to decrease the risk of privacy issues.

References:

To ensure the fulfillment of the privacy requirement when using the SmartNoise Python library, you need to set the epsilon value between 0 and 1. The SmartNoise library is designed to add differential privacy to a dataset by adding noise to the data, making it more difficult to identify individuals in the data. Differential privacy is achieved by setting a privacy budget, which is controlled by the epsilon value.

The epsilon value determines the amount of noise that is added to the data, and a smaller value of epsilon results in more privacy. However, too small of an epsilon value may lead to too much noise being added to the data, which can result in inaccurate results. Therefore, the value of epsilon should be chosen carefully based on the specific use case and the desired level of privacy.

Setting the epsilon value to -1 or setting delta to -1 is not recommended as it does not provide any meaningful privacy protection and can result in inaccurate results. Setting the epsilon value to 2 is also not recommended as it would result in a very large amount of noise being added to the data, which would lead to inaccurate results.

Therefore, the correct answer is option D: Set epsilon value between 0 and 1.