Data Classification

Overview#

Data Classification (Data Taxonomy) is part of Data Management and is the data taxonomy

Data Classification is the classification of data based on its level of sensitivity and the impact to the Organizational Entity or Personal Entity should that data be subject to Disclosure-Alteration-Destruction (DAD) without authorization.

Data Classification is required to:

Data Classification SHOULD to consider:

Data Classification may be determined by Trust Tiers as used within BeyondCorp's Zero Trust architecture

Data Classification requires Data Metadata (Well in Our Humble Opinion)

Data Classification#

Data Classification will vary depending each Organizational Entity's circumstances. However there are various areas that should be considered.

Data Classification types#

Data Classification types are wide and varied depending on the context

Some Data Classification types could be:

Microsoft Azure Data Classification recommendations [4]#

Microsoft recommends:

These "tags" are recommended be used always and used within Microsoft products (ie Word, Excel etc) and they are working with DLP vendors to recognizes and take appropriate actions based on these "default" Data Classification

NIST.SP.800-63 Data Classification#

Making certain attribute values available to a Relying Party can carry National Security implications. In situations where this may be the case, identification of such data values at the time of exchange can be absolutely crucial to ensuring that they are appropriately handled and protected during Data Management.

The NIST recommended values for use in Data Classification are:

As with all classified information, the determination of the classification level for any data must be made by the appropriate U.S. Federal Government authority and the integrity of this classification must be maintained as the data is transmitted or stored in by IT systems.

Data Classification Examples #

While each Entity Data Classification will be different it may be helpful to see Example Data Classification as shown below.

The Data Classification helps determine what baseline security controls are appropriate for safeguarding that data. All Organization data should be classified into one of three sensitivity levels, or classifications:

Restricted Data Example#

Data should be classified as Restricted when the unauthorized disclosure, alteration or destruction of that data could cause a significant level of risk to the Organization or its affiliates. Examples of Restricted data include: The highest level of security controls should be applied to Restricted data.

Private data Example#

Data should be classified as Private when the unauthorized disclosure, alteration or destruction of that data could result in a moderate level of risk to the Organization or its affiliates. By default, all Organization Data that is not explicitly classified as Restricted or Public data should be treated as Private data. A reasonable level of security controls should be applied to Private data.

Public data Example#

Data should be classified as Public when the unauthorized disclosure, alteration or destruction of that data would results in little or no risk to the University and its affiliates. Examples of Public data include press releases, sales brochures and advertising publications. While little or no controls are required to protect the confidentiality of Public data, some level of control is required to prevent unauthorized modification or destruction of Public data.

Data Classification of data should be performed by an appropriate Data Steward. Data Stewards are senior-level employees of the Organization who oversee the Data Management of one or more sets of Organization Data.

More Information#

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