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What this article shares with you is about what big data desensitization is. The editor thinks it is very practical, so I share it with you to learn. I hope you can get something after reading this article. Without saying much, follow the editor to have a look.

Big data desensitization, also known as data bleaching, data de-privacy or data deformation, refers to the deformation of some sensitive information through desensitization rules to achieve reliable protection of sensitive private data. as a result, desensitized real data sets can be safely used in development, testing and other non-production environments as well as outsourced environments.

Private data desensitization technology

Usually in the big data platform, the data is stored in a structured format, each table is composed of many rows, and each row of data is composed of many columns. Depending on the data properties of the column, data columns can usually be divided into the following types:

A column that can pinpoint a person is called an identifiable column, such as ID number, address, and name.

A single column cannot locate an individual, but multiple columns of information can be used to potentially identify a person. these columns are called semi-identifying columns, such as zip code, birthday, gender, etc. 87% of Americans can be identified using just zip code, birthday and gender information, according to a US research paper.

Columns that contain sensitive information about users, such as transaction volume, illness, and income.

Other columns that do not contain user sensitive information.

Privacy data disclosure type

Privacy data disclosure can be divided into many types, according to different types, we can usually use different privacy data disclosure risk models to measure the risk of preventing privacy data disclosure, and corresponding to different data desensitization algorithms to desensitize data. In general, the types of privacy data disclosure include:

Personal identification leaked. When the data user confirms in any way that a piece of data in the data table belongs to someone, it is called personal identity disclosure. Personal identification disclosure is the most serious, because in the event of personal identification disclosure, data users can get sensitive information about specific individuals.

Attribute disclosure is called attribute disclosure when data users learn about someone's new attribute information according to the data table they access. Personal identity disclosure will certainly lead to attribute disclosure, but attribute disclosure can also occur separately.

Membership leaked. When the data user can confirm that someone's data exists in the data table, it is called membership disclosure. The relative risk of membership disclosure is relatively small, personal identification disclosure and attribute disclosure must mean membership disclosure, but membership disclosure may also occur separately.

This is what big data desensitization is. The editor believes that there are some knowledge points that we may see or use in our daily work. I hope you can learn more from this article. For more details, please follow the industry information channel.

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