“Method And Apparatus For Generating Synthetic Data” in Patent Application Approval Process (USPTO 20220116199): Patent Application

2022 APR 29 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent application by the inventors CHO, Ji Hoon (Seoul, KR); HAN, Kyoo Hyung (Seoul, KR); KIM, Min Jung (Seoul, KR); KIM, Young Hyun (Seoul, KR); YOON, Hyo Jin (Seoul, KR), filed on October 13, 2021, was made available online on April 14, 2022, according to news reporting originating from Washington, D.C., by NewsRx correspondents.

This patent application has not been assigned to a company or institution.

The following quote was obtained by the news editors from the background information supplied by the inventors: “

“The following description relates to a technology for generating synthetic data.

“In data analysis, data combining is a widely used approach to improve the performance of analysis. However, it is virtually impossible for multiple organizations to share data containing personal information with each other and combine the data due to various regulations such as the Personal Information Protection Act, the General Data Protection Regulation (GDPR), and the Health Insurance Portability and Accountability Act (HIPPA). In order to avoid such legal regulations, de-identification techniques are often used, but even de-identified data has an increased risk of exposure after combining. In addition, in the related art, the data privacy protection technology uses encrypted (or protected) data, and thus a problem arises in that a method for satisfying the technology has to be devised according to an analysis query, which may lead to an increased time and complexity of the entire data analysis process.”

In addition to the background information obtained for this patent application, NewsRx journalists also obtained the inventors’ summary information for this patent application: “Embodiments disclosed in the present disclosure are to provide a method and apparatus for generating synthetic data.

“In one general aspect, there is provided an apparatus for generating synthetic data according to an embodiment including: a synthetic data generator configured to generate synthetic data corresponding to combined data obtained by combining original data held by each of a plurality of data providing apparatuses; and a synthetic data provider configured to provide the synthetic data to a data using apparatus.

“The synthetic data generator may receive a ciphertext for the original data from each of the plurality of data providing apparatuses, and generate the synthetic data based on the received ciphertext.

“The synthetic data generator may decrypt the ciphertext received from each of the plurality of data providing apparatuses in a trusted execution environment (TEE), generate the combined data by combining each original data piece generated through the decryption in the TEE, and generate the synthetic data based on the generated combined data in the TEE.

“The ciphertext for the original data may be a ciphertext generated by each of the plurality of data providing apparatuses by using a homomorphic encryption algorithm.

“The synthetic data generator may generate a ciphertext for the combined data by using the ciphertext received from each of the plurality of data providing apparatuses in an encrypted state, and generate a ciphertext for the synthetic data by using the ciphertext for the combined data in an encrypted state, and the synthetic data generator may provide the ciphertext for the synthetic data to the data using apparatus.

“The synthetic data generator may generate the synthetic data by using a multi-party computation protocol in which the plurality of data providing apparatuses participate.

“The synthetic data generator may generate the synthetic data by using a machine learning-based synthetic data generation model.

“The synthetic data generation model may be a pre-trained model to generate synthetic data satisfying differential privacy.

“In another general aspect, there is provided a method for generating synthetic data, the method including: generating synthetic data corresponding to combined data obtained by combining original data held by each of a plurality of data providing apparatuses; and providing the synthetic data to a data using apparatus.

“The generating may include receiving a ciphertext for the original data from each of the plurality of data providing apparatuses, and generating the synthetic data based on the received ciphertext, and generating the synthetic data based on the received ciphertext.

“The generating of the synthetic data based on the received ciphertext may include: decrypting the ciphertext received from each of the plurality of data providing apparatuses in a trusted execution environment (TEE); generating the combined data by combining each original data piece generated through the decryption in the TEE; and generating the synthetic data based on the generated combined data in the TEE.

“The ciphertext for the original data may be a ciphertext generated by each of the plurality of data providing apparatuses by using a homomorphic encryption algorithm.

“The generating of the synthetic data based on the received ciphertext may include: generating a ciphertext for the combined data by using the ciphertext received from each of the plurality of data providing apparatuses in an encrypted state; and generating a ciphertext for the synthetic data by using the ciphertext for the combined data in an encrypted state, and the providing may include providing the ciphertext for the synthetic data to the data using apparatus.

“The generating of the synthetic data may include generating the synthetic data by using a multi-party computation protocol in which the plurality of data providing apparatuses participate.

“The generating of the synthetic data may include generating the synthetic data by using a machine learning-based synthetic data generation model.

“The synthetic data generation model may be a pre-trained model to generate synthetic data satisfying differential privacy.”

The claims supplied by the inventors are:

“1. An apparatus for generating synthetic data, the apparatus comprising: a synthetic data generator configured to generate synthetic data corresponding to combined data obtained by combining original data held by each of a plurality of data providing apparatuses; and a synthetic data provider configured to provide the synthetic data to a data using apparatus.

“2. The apparatus of claim 1, wherein the synthetic data generator is further configured to receive a ciphertext for the original data from each of the plurality of data providing apparatuses, and generate the synthetic data based on the received ciphertext.

“3. The apparatus of claim 2, wherein the synthetic data generator is further configured to decrypt the ciphertext received from each of the plurality of data providing apparatuses in a trusted execution environment (TEE), generate the combined data by combining each original data piece generated through the decryption in the TEE, and generate the synthetic data based on the generated combined data in the TEE.

“4. The apparatus of claim 2, wherein the ciphertext for the original data is a ciphertext generated by each of the plurality of data providing apparatuses by using a homomorphic encryption algorithm.

“5. The apparatus of claim 4, wherein the synthetic data generator is further configured to generate a ciphertext for the combined data by using the ciphertext received from each of the plurality of data providing apparatuses in an encrypted state, and generate a ciphertext for the synthetic data by using the ciphertext for the combined data in an encrypted state; and the synthetic data provider is further configured to provide the ciphertext for the synthetic data to the data using apparatuses.

“6. The apparatus of claim 1, wherein the synthetic data generator is further configured to generate the synthetic data by using a multi-party computation protocol in which the plurality of data providing apparatuses participate.

“7. The apparatus of claim 1, wherein the synthetic data generator is further configured to generate the synthetic data by using a machine learning-based synthetic data generation model.

“8. The apparatus of claim 7, wherein the machine learning-based synthetic data generation model is a pre-trained model to generate synthetic data satisfying differential privacy.

“9. A method for generating synthetic data, the method comprising: generating synthetic data corresponding to combined data obtained by combining original data held by each of a plurality of data providing apparatuses; and providing the synthetic data to a data using apparatus.

“10. The method of claim 9, wherein the generating comprises: receiving a ciphertext for the original data from each of the plurality of data providing apparatuses; and generating the synthetic data based on the received ciphertext.

“11. The method of claim 10, wherein the generating of the synthetic data based on the received ciphertext comprises: decrypting the ciphertext received from each of the plurality of data providing apparatuses in a trusted execution environment (TEE); generating the combined data by combining each original data piece generated through the decryption in the TEE; and generating the synthetic data based on the generated combined data in the TEE.

“12. The method of claim 11, wherein the decrypting comprises using an encryption key shared in advance with each of the data providing apparatuses or a private key corresponding to a public key.

“13. The method of claim 10, wherein the ciphertext for the original data is a ciphertext encrypted using a symmetric key encryption algorithm or a public key encryption algorithm.

“14. The method of claim 11, wherein the ciphertext for the original data is a ciphertext encrypted using one selected from the group consisting of an advanced encryption standard algorithm (AES) and a data encryption standard algorithm (DES), Rivest, Shamir, Adleman (RSA) algorithm and an ElGamal algorithm.

“15. The method of claim 10, wherein the ciphertext for the original data is a ciphertext generated by each of the plurality of data providing apparatuses by using a homomorphic encryption algorithm.

“16. The method of claim 15, wherein the generating of the synthetic data based on the received ciphertext comprises: generating a ciphertext for the combined data by using the ciphertext received from each of the plurality of data providing apparatuses in an encrypted state; and generating a ciphertext for the synthetic data by using the ciphertext for the combined data in an encrypted state, and the providing comprises providing the ciphertext for the synthetic data to the data using apparatuses.

“17. The method of claim 9, wherein the generating of the synthetic data comprises generating the synthetic data by using a multi-party computation protocol in which the plurality of data providing apparatuses participate.

“18. The method of claim 9, wherein the generating of the synthetic data comprises generating the synthetic data by using a machine learning-based synthetic data generation model.

“19. The method of claim 18, wherein the machine learning-based synthetic data generation model is a pre-trained model to generate synthetic data satisfying differential privacy.”

URL and more information on this patent application, see: CHO, Ji Hoon; HAN, Kyoo Hyung; KIM, Min Jung; KIM, Young Hyun; YOON, Hyo Jin. Method And Apparatus For Generating Synthetic Data. Filed October 13, 2021 and posted April 14, 2022. Patent URL: https://appft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PG01&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.html&r=1&f=G&l=50&s1=%2220220116199%22.PGNR.&OS=DN/20220116199&RS=DN/20220116199

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