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Use Case
Data Masking

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Author
Loretta Jones
April 7, 2023
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FAQs

Which is more secure: data masking or tokenization?

No one can deny the value of data for today’s organizations. With the ongoing rise of data breaches and cyber attacks, it is increasingly essential for organizations to protect sensitive data from unauthorized access, use, disclosure, modification, or destruction. Data security is the practice of implementing measures to ensure the confidentiality, integrity, and availability of data to the appropriate end users.
There are many techniques used in data security. In this article, we’ll focus on data privacy and two of the most popular approaches in protecting sensitive data: data masking and tokenization. At their essence, these are both techniques for generating fake data, but they are achieved in distinct, technically complex ways, and it is essential to understand their differences in order to choose the right approach for your organization.

Which is more secure: data masking or tokenization?

No one can deny the value of data for today’s organizations. With the ongoing rise of data breaches and cyber attacks, it is increasingly essential for organizations to protect sensitive data from unauthorized access, use, disclosure, modification, or destruction. Data security is the practice of implementing measures to ensure the confidentiality, integrity, and availability of data to the appropriate end users.
There are many techniques used in data security. In this article, we’ll focus on data privacy and two of the most popular approaches in protecting sensitive data: data masking and tokenization. At their essence, these are both techniques for generating fake data, but they are achieved in distinct, technically complex ways, and it is essential to understand their differences in order to choose the right approach for your organization.

Which is more secure: data masking or tokenization?

No one can deny the value of data for today’s organizations. With the ongoing rise of data breaches and cyber attacks, it is increasingly essential for organizations to protect sensitive data from unauthorized access, use, disclosure, modification, or destruction. Data security is the practice of implementing measures to ensure the confidentiality, integrity, and availability of data to the appropriate end users.
There are many techniques used in data security. In this article, we’ll focus on data privacy and two of the most popular approaches in protecting sensitive data: data masking and tokenization. At their essence, these are both techniques for generating fake data, but they are achieved in distinct, technically complex ways, and it is essential to understand their differences in order to choose the right approach for your organization.
Loretta Jones
VP of Growth
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