System and method for anonymized data repositories

1. A method, comprising:

identifying, via an anonymization server, a data repository storing personal identification information (PII) data;

determining, via the anonymization server, that an anonymity value associated with the data repository is below a threshold;

generating, via the anonymization server, synthetic data to add to the data repository to achieve the anonymity value;

creating, via the anonymization server, an anonymized data repository clone based on the synthetic data and anonymized PII data; and

storing, via the anonymization server, the synthetic data into the anonymized data repository clone.

2. The method of claim 1 , wherein the anonymity value comprises a minimum k-homogeneity value.

3. The method of claim 1 , comprising generating a configuration file indicating a portion of the data repository to anonymize; and wherein identifying the data repository storing PII data comprises identifying the portion of the data repository in response to generating the configuration file.

4. The method of claim 1 , wherein creating, via the anonymization server, the anonymized data repository clone based on the synthetic data and the PII data comprises:

anonymizing, via the anonymizer server, the PII data to create the anonymized PII data by applying one-way data masking, one-way data morphing, or a combination thereof; and

storing the anonymized data into the anonymized data repository clone.

5. The method of claim 1 , wherein the synthetic data comprises random values associated with the PII data.

6. The method of claim 1 , wherein the anonymity value comprises a k-homogeneity value, and wherein determining, via the anonymization server, that the anonymity value associated with the data repository is below the threshold, comprises:

receiving a request to anonymize the data repository, wherein the request comprises an I-diversity value;

deriving the minimum k-homogeneity value based on the l-diversity value; and

determining that the k-homogeneity value is below a threshold.

7. The method of claim 1 , wherein creating, via the anonymization server, the anonymized data repository clone based on the synthetic data and the PII data comprises:

anonymizing, via the anonymizer server, the PII data to create the anonymized PII data by applying a data grouping, wherein applying the data grouping comprises grouping related fields in the PII data into a single field in the anonymized data; and

storing the anonymized data into the anonymized data repository clone.

8. A computing system, comprising:

a memory storing personal identification information (PII) data; and

an anonymizer server communicatively coupled to the memory, wherein the anonymizer server is configured to perform operations comprising:

receiving a repository configuration request for an anonymized data repository clone comprising an anonymized data schema and an anonymity value indicating a measure of anonymity;

creating the anonymized data repository clone based on the anonymized data schema and the anonymity value;

storing synthetic data in the data repository to achieve the anonymity value;

anonymizing the PII data to create anonymized data; and

storing the anonymized data and the synthetic data in the anonymized data repository clone.

9. The computing system of claim 8 , where anonymizing the PII data comprises applying one-way data masking, one-way data morphing, data grouping, or a combination thereof, and wherein applying the data grouping comprises grouping related fields in the PII data into a single field in the anonymized data.

10. The computing system of claim 8 , wherein the anonymity value is based on an l-diversity value, a k-anonymity value, or a combination of the l-diversity value and the k-anonymity value.

11. The computing system of claim 8 , wherein the synthetic data comprises random values associated with the PII data.

12. The computing system of claim 8 , wherein the repository configuration request comprises an anonymization technique and wherein the PH data is anonymized using the anonymization technique.

13. The computing system of claim 8 , wherein the repository configuration request is submitted via one or more inputs received via a graphical user interface (GUI).

14. A non-transitory, computer-readable medium storing instructions executable by a processor of a computing system, the instructions configured to:

receive a repository configuration request comprising an anonymized data schema and an anonymity value;

generate synthetic data to add to an anonymized data repository clone based on the anonymized data schema and the anonymity value;

create the anonymized data repository clone based on the anonymized data schema and the synthetic data;

anonymize PII data to create anonymized data by applying a one-way data masking, one-way data morphing, or a combination thereof;

store the anonymized data in the anonymized data repository clone; and

store the synthetic data in the anonymized data repository clone.

15. The computer-readable medium of claim 14 , wherein the synthetic data is configured to increase the anonymity value.

16. The computer-readable medium of claim 14 , wherein the synthetic data comprises random values associated with the PII data.

17. The computer-readable medium of claim 14 , wherein the anonymity value comprises an l-diversity value, a k-anonymity value, or any combination thereof.

18. The computer-readable medium of claim 14 , wherein the anonymity value comprises a k-homogeneity value and wherein the repository configuration request comprises an l-diversity value, and wherein generating synthetic data, comprises:

deriving the minimum k-homogeneity value based on the l-diversity value;

determining that the k-homogeneity value is below a threshold; and

generating synthetic data to achieve the anonymity value based on the k-homogeneity value and the threshold.

19. The computer-readable medium of claim 14 , wherein the repository configuration request comprises an anonymization technique and wherein the PII data is anonymized using the anonymization technique.

20. The computer-readable medium of claim 14 , wherein anonymizing the PII data comprises applying data grouping, wherein applying the data grouping comprises grouping related fields in the PII data into a single field in the anonymized data.