HEaaN Homomorphic Analytics concept

Available in VPC

This guide describes the HEaaN Homomorphic Analytics service's structure and homomorphic encryption which is its core technology to help you understand and use the service better.

Understanding homomorphic encryption technology

The homomorphic encryption technology which is the core of HEaaN Homomorphic Analytics is a technology that computes encrypted data without decrypting it. It has the advantage of maintaining data privacy, as only the result of the data computation is decrypted to be viewed.

Using a conventional method where you decrypt the encrypted data, compute, and encrypt the result again, the important data is not protected while the computation takes place. Furthermore, such method of data processing may violate laws related to data protection in certain areas.

Such problems in the conventional method can be resolved by performing computations while the data is encrypted using the homomorphic encryption technology. By maintaining the encrypted status, various personal and public data can be securely protected from hacking threats, as well as being able to perform various tasks such as computation, statistics, analysis, combination, etc., without having to worry about invasion of data privacy.

HEaaN Homomorphic Analytics Structure

The composition of the HEaaN Homomorphic Analytics service provided by NAVER Cloud Platform is as follows.

• Key
  HEaaN Homomorphic encryption key to use in Homomorphic Analytics. It is used to encrypt and decrypt data, and perform homomorphic computation according to homomorphic encryption algorithms on the cloud. Create this before all others in order to use the service.

• Data
  The target data to operate on using HEaaN Homomorphic Analytics. You can use the homomorphic encryption key created on the cloud to encrypt the uploaded data, or upload the data that is already encrypted locally.

• Project
  A work space you create to perform computations using the uploaded data. One project is made up of multiple tasks.

• Process
  Create a task by setting up computing method and target data, and execute the task to perform computations.

• Instance
  An independent analysis environment to enable data analysis with Python code using Jupyter Notebook.